Current Perspectives on Augmented Reality and Head-Mounted Displays in Endoscopy: A Scoping Review

Current Perspectives on Augmented Reality and Head-Mounted Displays in Endoscopy: A Scoping Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Current Perspectives on Augmented Reality and Head-Mounted Displays in Endoscopy: A Scoping Review Mingwei Cui, Xiaorong Gao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8098102/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Augmented reality–enabled head-mounted displays (AR-HMDs) are emerging as alternative visualization interfaces in endoscopic surgery. This scoping review maps current applications, methodological characteristics, and performance trends of AR-HMDs across different procedural contexts. Methods Following the PRISMA-ScR framework, peer-reviewed articles published between 2014 and 2025 were searched in Web of Science, Scopus, PubMed, and IEEE Xplore. Thirty-six studies met inclusion criteria and were charted using a predefined data framework that categorized HMD configurations by registration type and imaging dimension. A qualitative Likert-scale evaluation further compared six representative configurations across visibility, usability, and latency dimensions. Results AR-HMDs have been applied in endoscopic, laparoscopic and thoracic, transluminal and endoluminal procedures, enhancing spatial awareness, navigation precision, and training efficiency. Head-anchored systems provide optimal responsiveness and easy o setup, whereas world- and object-anchored setups enable more immersive 3D integration with anatomical structures. Discussion Evidence indicates that AR-HMDs can enhance visibility, usability, and cognitive efficiency compared with traditional displays, though challenges remain in latency, ergonomics, and setup complexity. Further technical optimization is needed before these systems can achieve wider clinical adoption. Conclusion AR-HMDs have demonstrated promising applicability across various endoscopic procedures and may play an increasingly important role in enhancing visualization and workflow efficiency as technical and ergonomic limitations are further addressed. Head-mounted displays augmented reality endoscopy surgical navigation 3D visualization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Background Endoscopy is a medical technique that enables internal visualization and access to organs and tissues through natural orifices or small incisions, allowing both diagnostic and interventional procedures without the need for open surgery. By avoiding the extensive tissue disruption characteristic of open surgery, endoscopic approaches substantially reduce patient trauma, recovery time, and hospitalization, contributing to improved clinical outcomes (Liawrungrueang et al., 2025 ; Patil et al., 2024 ; Qadrie et al., 2025 ). Owing to these advantages, endoscopy has become an essential technique across diverse clinical domains, including gastrointestinal, respiratory, urological, and neurosurgical interventions (Jitpakdee et al., 2023 ). In endoscopic procedures, the operative site is spatially separated from the visual feedback displayed on an external monitor (Fig. 1 ). This indirect visualization requires surgeons to frequently alternate their gaze between the patient and the screen, disrupting natural hand–eye coordination and increasing both cognitive and physical workload. Consequently, improving the immediacy and spatial integration of visual feedback has become a central focus for developing next-generation visualization technologies in endoscopy. As summarized in Table 1 , endoscopic techniques can be broadly classified into three procedural categories—general endoscopic surgery, laparoscopic and thoracoscopic surgery, and transluminal or endoluminal surgery—based on their anatomical access routes and operative environments. General endoscopic surgery (Fig. 1 a) involves rigid or semi-rigid scopes used within confined spaces such as the brain ventricles or joint cavities. Laparoscopic and thoracoscopic surgery (Fig. 1 b) employs rigid rod-lens endoscopes inserted through small incisions to operate inside insufflated abdominal or thoracic cavities, representing the most established form of minimally invasive surgery (Marks, 2012 ). Transluminal and endoluminal surgery (Fig. 1 c), in contrast, uses flexible scopes introduced through natural orifices to access internal lumens of organs such as the gastrointestinal or respiratory tracts (McCarty, 2023 ). Within this framework, augmented reality (AR) and head-mounted displays (HMDs) have been increasingly explored as potential interfaces to enhance spatial awareness, visual ergonomics, and procedural efficiency in endoscopic environments. Table 1 Clinical and technical characteristics of three categories of endoscopic procedures. Aspect General Endoscopic Surgery Laparoscopic and Thoracoscopic Surgery Transluminal and Endoluminal Procedure Entry Route Small incision Small incision (with trocar port for sealing gas) Natural orifice (mouth, urethra, anus, etc.) Operative Site Confined anatomical cavities (e.g., cranial ventricles, joints) Insufflated abdominal, thoracic, or pelvic cavities, Natural lumens (respiratory, gastrointestinal, or urinary tracts) Primary Purpose Diagnostic or localized therapeutic procedures Surgical interventions Diagnostic and interventional procedures Representative Use Cases Cranial neurosurgery, ventriculostomy, arthroscopy Thoracoscopy, cholecystectomy, appendectomy, hernia repairs Bronchoscopy, gastrointestinal polypectomy, ERCP, Ureteroscopy Endoscope Type Rigid or semi-rigid endoscopes Rigid rod-lens endoscopes Flexible or rigid fiber-optic endoscopes Ancillary Tools Specialized endoscopic instruments Graspers, dissectors, retractors Biopsy or ablation devices Operational Technique Navigation and manipulation of the endoscope within confined spaces Hand-eye coordination to manipulate multiple rigid instruments, precise control Navigation and control of scopes Complexity Moderate High Variable Procedure Duration Moderate Moderate to long Short to moderate Learning Curve Moderate Steep Moderate ERCP: Endoscopic Retrograde Cholangiopancreatography 1.1. Categories of Head-Mounted Displays Head-mounted displays (HMDs) have been explored as an alternative to conventional surgical monitors for intraoperative visualization. By presenting critical visual information within the user’s direct line of sight, HMDs minimize the need for head and gaze shifts, improving ergonomic alignment and potentially reducing musculoskeletal strain during prolonged procedures (Doughty et al., 2022 ; Johnson et al., 2022 ; Maithel et al., 2005 ; Qian et al., 2017 ). HMDs can be categorized into two types according to their visualization mechanism: optical see-through (OST) and video see-through (VST) systems (Rolland et al., 1994 ), as illustrated in Fig. 2 . OST-type HMDs (Fig. 2 a) superimpose computer-generated imagery onto the user’s natural view through transparent or semi-transparent optical elements—often holographic waveguides or related components (Hong et al., 2011 ). This configuration preserves natural stereo vision and depth cues, offering intuitive situational awareness in clinical environments, but it is constrained by limited field of view (FOV), reduced display brightness, and diminished contrast of virtual elements due to optical projection. By contrast, VST-type HMDs (Fig. 2 b) use forward-facing cameras to capture the real environment and digitally combine it with virtual overlays on opaque displays. This architecture enables fine control over the degree of visual immersion and supports augmented reality (AR), mixed-reality (MR), virtual reality (VR) presentation along the reality–virtuality continuum (Milgram & Kishino, 1994 ). VST systems typically provide higher-resolution virtual imagery and wider FOVs than OST devices, but their reliance on camera input introduces inherent latency and may reduce the fidelity of real-world visuals, depending on camera performance and on-device processing. 1.2. Value of HMDs for Endoscopic Procedures During endoscopic procedures, physicians manipulate surgical instruments through natural orifices or small incisions while relying on real-time endoscopic information—including video streams of the operative site and the patient’s vital parameters—for spatial orientation and decision-making. In contrast to conventional endoscopic monitors which are positioned at a distance from the operative field, HMDs—including both OST and VST types—present visual information directly within the user’s line of sight, naturally integrating virtual content with the surrounding environment and thereby improving workflow continuity. Each category of HMD provides distinct advantages. OST-type HMDs project digital overlays onto transparent optics, allowing surgeons to maintain direct visual contact with the patient and operative field. This mechanism preserves natural depth perception and situational awareness with minimal obstruction, making it particularly useful in procedures where augmented content supports rather than dominates visual guidance. However, optical projection imposes physical limitations—restricted field of view (FOV) and limited brightness—that constrain the fidelity of rendered information. Alternatively, VST-type HMDs capture the surrounding environment via forward-facing cameras and digitally merge it with high-resolution virtual content on opaque displays. This configuration is advantageous for tasks emphasizing detailed visualization of the endoscopic scene, though the added computational load and device weight may contribute to operator fatigue during long procedures. To assess the technological readiness of these two categories for endoscopic use, representative AR HMDs were examined. Table 2 summarizes the key specifications of commercially available or investigational devices, including HMD type, processing power (processor and memory), display quality (display type, resolution, refresh rate, and FOV), software platform (OS), and form factor (weight and fixture). Presented chronologically, the table illustrates the steady evolution of HMD technology toward higher processing capabilities and improved visual performance—developments that are critical for supporting real-time high-definition endoscopic video and ensuring system stability in image-intensive surgical environments. Table 2 Technical specifications and chronological overview of augmented-reality head-mounted display (AR-HMD) devices. Year of Release Device HMD type Processor Memory Display type Resolution (per eye) Refresh Rare FOV (Diagonal) OS Wearable weight Fixture 2011 Sony HMZ-T1 VST N/A (video source needed) N/A OLED 1280 x 720 60 Hz 45° (horizontal) N/S 420 g Headband 2013 Sony HMS-3000MT VST N/A (video source needed) N/A OLED 1280 x 720 60 H 45° (horizontal) N/S 480g Overhead strap 2014 Epson Moverio BT-200 OST 2 x 1.2 GHz, TI OMAP 4460 1 GB LCD 960 x 540 60 Hz 23° Android 88 g Ear hook 2016 ODG R-7 OST 4 x 2.7 GHz, Qualcomm Snapdragon 805 3 GB LCoS 1280 x 720 100 Hz 30° ReticleOS (Android) 125 g Overhead strap, ear hook 2016 Microsoft HoloLens OST 4 x 1.84 GHz, Intel Atom x5-Z8100 2 GB LCoS 1268 x 720 60 Hz 34° Windows Holographic 579 g Overhead strap 2016 Brother’s AiRScouter WD-200B OST N/A (video source needed) N/A LCD 1280 x 720 60 Hz 17.8° N/S 145 g Headband 2018 Epson Moverio BT-35E OST 2 x 2.5 GHz, 6 x 1.7 GHz, Qualcomm Snapdragon XR1 4 GB LCD 1280 x 720 30 Hz 30° Android 119 g Overhead strap 2018 Samsung Odyssey+ VST N/A (video source needed) N/A AMOLED 1600 ×1440 90 Hz 101° (horizontal) SteamVR, Windows Mixed Reality 590 g Headband 2018 Magic Leap 1 OST Nvidia Parker SoC 8 GB LCoS 1280 x 960 122 Hz 50° Lumin OS 316g Headband 2019 Oculus Quest V1 VST 4 x 2.45 GHz, 4 x 1.9 GHz, Qualcomm Snapdragon 835 4 GB OLED 1600 ×1440 72 Hz 115° Android 571 g Headband 2019 Microsoft HoloLens 2 OST 4x 2.96 GHz, 4 x 1.8 GHz, Qualcomm Snapdragon 850 4 GB LBS 1440 x 936 60 Hz 52° Windows Holographic 556 g Headband 2019 Valve index VST N/A (PC-powered) N/A LCD 1600 ×1440 144 Hz 114° N/S 809 g Headband 2019 MAD Gaze GLOW Plus OST N/A (PC-powered) N/A OLED 1920 x 1080 60 Hz 45° Android 92 g Rigid arms 2021 HTC Vive Pro 2 VST N/A (PC-powered) N/A LCD 2448 x 2448 120 Hz 113° N/S 850g Headband 2023 Meta Quest 3 VST 1 x 3.19 GHz, 4 x 2.8 GHz, 3 x 2.0 GHz, Qualcomm Snapdragon XR2 Gen 2 8 GB LCD 2064 x 2208 120 Hz 110° (horizontal) Android 515 g Headband 2024 Apple Vision Pro VST 4 x 3.5 GHz, 4 x 2.4 GHz, Apple M2 + R1 chip 16 GB Micro-OLED 3660 x 3200 100 Hz ~ 100° (horizontal) visionOS 650 g Headband 2024 Pico 4 ultra VST 1 x 3.19 GHz, 4 x 2.8 GHz, 3 x 2.0 GHz, Qualcomm Snapdragon XR2 Gen 2 12 GB LCD 2160 x 2160 90 Hz 122° Pico OS (Android) 580 g Headband OST: optical see-through, VST: video see-through, FOV: fields of view, OS: operating system, OLED: Organic Light Emitting Diode, LCD: Liquid Crystal Display, LCoS: Liquid Crystal on Silicon, LBS: Laser Beam Scanning, PC: personal computer, N/S: not specified. 1.3. Value of AR for Endoscopic Procedures Building on advances in medical imaging segmentation and three-dimensional (3D) reconstruction technologies, augmented reality (AR) provides an effective solution for enhancing intraoperative visualization in endoscopy. Pre-procedural high-resolution computed tomography (CT) or magnetic resonance imaging (MRI) data can be pre-processed into 3D models to guide navigation and support interactive surgical planning (Eberhardt et al., 2010 ; Huang et al., 2019 ; Lachkar et al., 2018 ; Tamiya et al., 2013 ). However, traditional endoscopy relies on two-dimensional (2D) video displays that lack depth cues, often causing visual strain and surgeon fatigue during prolonged operations in confined spaces (Thavarajasingam et al., 2022 ). The integration of AR and virtual reality (VR) capabilities into head-mounted displays (HMDs) enhances visualization beyond conventional monitors, providing immersive and spatially coherent feedback (Kassutto et al., 2021 ; Rad et al., 2022 ; Weidert & Stefan, 2022 ). Whereas VR systems offer fully enclosed immersion, AR is better suited for clinical endoscopy because it allows preoperative 3D models or surgical guidance data to be overlaid directly onto intraoperative views (Li et al., 2019 ; Linxweiler et al., 2020 ; Okachi et al., 2022 ; Tabrizi & Mahvash, 2015 ). This alignment reduces the need for gaze shifts between monitors and the operative field (Fig. 1 ), a major source of cognitive and physical fatigue (Doughty et al., 2022 ; Eberhardt et al., 2010 ; Johnson et al., 2022 ). By centralizing visual and contextual information, AR-HMDs enhance workflow efficiency (L. Qian et al., 2019 )(Fang et al., 2023 ; Okachi et al., 2022 ), improve hand–eye coordination, depth perception, and reduce cognitive load through unified spatial presentation (Sadeghi et al., 2022 ; Suter et al., 2023 ). AR-HMDs also improve surgical navigation and spatial orientation, particularly in complex or minimally accessible procedures. The fusion of preoperative and intraoperative data within the surgeon’s field of view strengthens spatial correspondence between medical imagery and the patient’s anatomy (Hwang & Son, 2022 ; Li et al., 2019 ; Matsuoka et al., 2014 ; Okachi et al., 2022 ; Pelizzo et al., 2022 ; L. Qian et al., 2019 ). Such visualization facilitates precise tool positioning and real-time guidance. In a prospective randomized controlled clinical trial, Linxweiler et al. demonstrated in a prospective, randomized, controlled clinical trial that AR-enhanced navigation software was well received by surgeons across different experience levels and improved usability in endoscopic sinus surgery, without prolonging operative time or increasing complication rates (Linxweiler et al., 2020 ). In summary, recent developments in HMDs and AR technologies are transforming how visual information is presented and perceived in endoscopic procedures. Both VST and OST systems offer complementary advantages for different clinical scenarios, while AR provides greater utility than VR by preserving direct intraoperative visualization. When combined, AR-HMDs function as an integrated display platform that can enhance spatial awareness, procedural efficiency, and overall workflow in endoscopic practice. 2. Methods Preliminary examination of the literature indicated that the application of augmented reality head-mounted displays (AR-HMDs) in endoscopy remains a relatively new research area. The available studies are limited in number, heterogeneous in design, and often lack consistent quantitative measurements of system performance. As a result, a quantitative synthesis in the format of a systematic review was not feasible. Therefore, a scoping review approach was adopted to comprehensively summarize and map the existing research, with the aim of identifying current applications, knowledge gaps, and methodological trends in this emerging field. This review was conducted in accordance with the PRISMA-ScR guidelines, which provide a transparent methodological framework to ensure comprehensive and reproducible reporting (Tricco et al., 2018 ). Following these guidelines, the review proceeded through five sequential phases: (1) identifying the research question, (2) identifying relevant studies, (3) study selection, (4) charting the data, and (5) collating, summarizing, and reporting the results. The optional “consultation exercise” step was not performed, as it was considered unnecessary given the exploratory scope of this review. 2.1. Research Question To ensure a structured and comprehensive mapping of existing knowledge, this review was guided by the central question: What is the role of augmented reality (AR) and head-mounted displays (HMDs) in endoscopy? Based on this question, the review discusses current clinical applications, benefits, limitations, and future directions of AR-enabled HMDs in various endoscopic procedures. 2.2. Literature Search A comprehensive literature search was performed in four major databases: Web of Science, Scopus, PubMed, and IEEE Xplore. Customized search strings were developed using Boolean operators and database-specific syntax to locate relevant articles, and the publication period was limited to 2014–2025. The search strings used are presented in Supplementary File 1. During the search process in each database, letters, patents, grants, abstracts, book chapters, theses etc. were excluded to retain only peer-reviewed articles for further screening. Review articles were initially included to provide contextual understanding but were excluded during the screening phase. All citations were imported into the bibliographic management software EndNote 2025 (Clarivate, Philadelphia, PA, USA) for efficient organization, deduplication, and subsequent reference management. Duplicated citations were identified using EndNote ’s “Library – Find Duplicates” function and manually removed, with further duplicates manually identified and removed when found later in the process. 2.3. Study Selection To ensure focused inclusion, only peer-reviewed articles addressing the application of AR-HMDs in endoscopic procedures were selected. Studies were excluded if they did not address all three key aspects — AR, HMD, and endoscopy — or were published in languages other than English. References in the included articles were also reviewed to identify additional relevant articles. In cases where the same research was reported in multiple publications, only the most recent article was retained for inclusion. The selection process is summarized in the PRISMA-ScR workflow diagram shown in Fig. 3 , which outlines the number of records identified, screened, and included at each stage. * The original identification included articles, clinical trials, comparative studies, meeting papers, case reports and reviews published between 2014 and 2025, while excluding letters, patents, grants, abstracts, book chapters, and theses. ** Additional records (N = 5) were identified through reference scanning during the screening phase and subsequently included in the full-text eligibility assessment. As shown in Fig. 3 , after the removal of duplicate records across databases, 181 unique articles were retained for screening. A two-stage screening process was then applied to ensure the inclusion of relevant studies. In the first stage, titles and abstracts were manually reviewed, resulting in the exclusion of 142 records that were unrelated to either endoscopy or HMDs. In the second stage, 39 full-text articles were assessed for eligibility; 8 were subsequently excluded due to irrelevance, while 5 additional records were identified through reference scanning. Ultimately, 36 studies met the inclusion criteria and were incorporated into this scoping review, comprising 28 journal articles and 8 conference proceedings for data charting and synthesis. 2.4. Data Charting Framework To ensure a structured and reproducible synthesis, the data charting framework for this scoping review was defined a priori to capture both the technical and procedural dimensions of head-mounted display (HMD) applications in endoscopy, while ensuring methodological transparency and consistency during evidence synthesis. Specifically, we categorized each study according to the type of registration—head-anchored (H-A), world-anchored (W-A), or object-anchored (O-A)—and by image dimension (2D or 3D), following the technical taxonomy from Qian at al. (Qian et al., 2017 ). Table 3 summarizes the six resulting combinations that describe how information can be registered and displayed through HMDs in endoscopic contexts. Table 3 Categorization of HMD-displayed information in endoscopy by registration type and image dimension. Registration 2D 3D H-A 2D information fixed at the same position in the HMD view. • Intraoperative vital signs, e.g., heart rate, blood pressure, oxygen saturation. 3D information fixed at the same position in the HMD view. • Static 3D model reconstructed from preoperative image, e.g., 3D skull. W-A 2D overlays aligned with specific position in the environment: • Virtual 2D view reconstructed from preoperative image, anchored in the air, e.g., virtual bronchoscopy. • 2D video stream from intraoperative endoscopic camera, e.g., bronchoscopic view, laparoscopic view. 3D overlays aligned with specific position in the environment: • 3D model reconstructed from preoperative image, e.g., 3D airway tree, 3D ventricle. O-A 2D overlays aligned with specific landmarks: • Preoperative image slices, anchored to the patient’s anatomy, e.g., CT, MR • 2D video stream from intraoperative endoscopic camera, e.g., bronchoscopic view, laparoscopic view. 3D overlays aligned with specific landmarks: • 3D model reconstructed from preoperative image, e.g., 3D airway tree, 3D ventricle. • 3D point cloud reconstructed from intraoperative endoscopic camera, e.g., 3D point cloud from binocular endoscope. Categorized based on the technical classification method adapted from previous research ( Qian et al., 2017 ). H-A: head-anchored, W-A: world-anchored, O-A: object-anchored. Each of the six configurations represents a specific balance between user-centered perception and system-centered spatial alignment. For example, head-anchored (H-A) displays prioritize continuous access to intraoperative data within the surgeon’s field of view, whereas world-anchored (W-A) and object-anchored (O-A) systems enable spatially aligned overlays that correspond to environmental or anatomical landmarks. This predefined taxonomy provides both a conceptual basis for comparing technical implementations and a methodological foundation for subsequent data synthesis. Building upon these six configurations, the following Results section (Table 4 ) summarizes the extracted studies in terms of HMD device type, AR registration method, endoscopic procedure category, and reported system performance parameters. 2.5. Evaluation Framework Building upon the categorization described above, a qualitative evaluation framework was developed to enable consistent comparison across the six HMD categories identified (H-A 2D/3D, W-A 2D/3D, O-A 2D/3D). This framework aimed to synthesize the diverse usability and performance information extracted from the included studies and to facilitate structured interpretation of the comparative results. While some studies reported standardized subjective workload assessments such as the NASA Task Load Index (NASA-TLX), most provided only qualitative descriptions of user experience or technical performance. Because quantitative measurements (e.g., display latency, registration accuracy) were inconsistently reported, a structured yet interpretive framework was adopted to maintain methodological coherence across studies. Six evaluation aspects—Visibility, Ease of Setup, Ease of Use, Cognitive Efficiency, Latency, and Adaptability—were defined to capture both user-centered and system-centered characteristics relevant to endoscopic AR-HMD applications. While this framework conceptually aligns with several workload dimensions of NASA-TLX—such as mental demand, effort, and performance—it was not intended as a direct adaptation of that scale. Rather, it extends these constructs to incorporate system-level and contextual usability factors (e.g., visibility, latency, adaptability) that are essential for evaluating AR-HMD operation within endoscopic environments. Each AR-HMD configuration was initially rated independently by both authors, based on the synthesized evidence extracted from the included studies. Any discrepancies were resolved through iterative discussion until a consensus score was achieved for each evaluation aspect. The final ratings therefore represent an expert consensus–based qualitative assessment, reflecting interpretive synthesis rather than quantitative measurement. 3. Results After the rigorous study selection process in Section 2.3 , a total of 36 studies published between 2018 and 2025 met the inclusion criteria and were charted according to the predefined data charting framework described in Section 2.4 . Table 4 summarizes the extracted data across all included studies, outlining their respective HMD devices, AR registration methods, type of endoscopic application, study subjects, and reported system performance metrics. Table 4 Summary of recent studies on the application of augmented reality (AR) head-mounted displays (HMDs) in endoscopic procedures. Article HMD HMD Type AR Registration Content Displayed Endoscopic Procedure Study Subject System Latency (ms) Carbone et al. ( 2018 ) Microsoft HoloLens OST O-A 3D Endoscopic surgery (Cranial) Phantom N/S Jayender et al. ( 2018 ) Oculus Rift Development Kit 2 (with custom camara module for VST feature) VST W-A 3D Laparoscopic surgery Phantom (peg transfer) N/S Qian, L. et al. ( 2018 ) Microsoft HoloLens OST O-A 3D Laparoscopic surgery Phantom 220.81 ± 25.54 (640 × 480 pixels) Xu et al. ( 2018 ) Sony HMZ-T1 OST H-A 2D Laparoscopic surgery 21 Patients N/S Huber et al. ( 2019 ) Microsoft HoloLens OST H-A 2D Endoluminal procedure (Rectoscopy) Patient N/S Jiang et al. ( 2019 ) Microsoft HoloLens OST W-A 3D Laparoscopic surgery Phantom (peg transfer) N/S Li et al. ( 2019 ) Microsoft HoloLens OST W-A 3D Endoscopic surgery (Cranial) Patient N/S Lohou et al. ( 2019 ) Microsoft HoloLens OST W-A 3D Thoracoscopic Surgery 1 volunteer (pre-clinical) N/S Qian, L. et al. ( 2019 ) Microsoft HoloLens OST O-A 3D Laparoscopic surgery Phantom (peg transfer) 337.2 ± 31.7 (1080 × 680 pixels) Qian, M. et al. ( 2019 ) ODG R-7 OST H-A 2D Endoluminal procedure (Laryngoscopy) Phantom “Minimal latency” Al Janabi et al. ( 2020 ) Microsoft HoloLens OST W-A 2D Endoluminal procedure (Ureteroscopy) Phantom N/S Qian, L. et al. ( 2020 ) Microsoft HoloLens OST O-A 3D Laparoscopic surgery Phantom (peg transfer) N/S Shen et al. ( 2020 ) Sony HMS-3000MT OST O-A 3D Laparoscopic surgery Phantom N/S Ivan et al. ( 2021 ) Microsoft HoloLens OST O-A 3D Endoscopic surgery (Cranial) 11 Patients N/S Liu et al. ( 2021 ) Microsoft HoloLens OST W-A 3D Endoscopic surgery 44 Patients N/S West et al. ( 2021 ) Microsoft HoloLens 2 OST O-A 3D Transluminal procedure (Aortic intervention) Porcine model N/S Arpaia et al. ( 2022 ) Microsoft HoloLens 2 OST W-A 2D Laparoscopic Surgery Simulated surgery 0.9–1.1 (vitals only) Khan et al. ( 2022 ) Microsoft HoloLens 2 OST W-A 2D Endoscopic surgery Cadaver 150 Ma et al. ( 2022 ) Microsoft HoloLens OST O-A 3D Laparoscopic surgery Phantom N/S Mak et al. (2022) Microsoft HoloLens OST H-A 2D Endoscopic surgery Phantom N/S Okachi et al. ( 2022 ) Epson Moverio BT-35E OST H-A 2D Endoluminal procedure (Optical-navigated Bronchoscopy) Phantom N/S Song et al. ( 2022 ) Microsoft HoloLens 2 OST O-A 3D Endoscopic surgery (Hip arthroscopy) Phantom N/S Stewart et al. ( 2022 ) Microsoft HoloLens OST H-A 3D Laparoscopic surgery Phantom N/S Torabinia et al. ( 2022 ) Microsoft HoloLens 2 OST W-A 3D Laparoscopic surgery (Myomectomy) Bovine model N/S Zhang et al. ( 2022 ) Microsoft HoloLens OST H-A 2D Endoscopic surgery (Cranial) 20 Patients (telemedicine) Max 230 (4G connection), Max 26 (5G connection) Fang et al. ( 2023 ) MAD Gaze GLOW Plus OST H-A 2D Endoscopic surgery (Knee arthroscopy) Phantom < 50 Fu et al. ( 2023 ) Microsoft HoloLens OST W-A 2D Laparoscopic surgery Phantom N/S Kildahl-Andersen et al. ( 2023 ) Microsoft HoloLens 2 OST H-A 2D Endoluminal procedure (EM-navigated Bronchoscopy) Phantom, Patient 330–350 Peng et al. ( 2023 ) Microsoft HoloLens OST W-A 3D Endoscopic surgery (Cranial) Phantom N/S Acar et al. ( 2024 ) Microsoft HoloLens 2 OST O-A 2D Endoluminal procedure (Ureteroscopy) Phantom N/S Forseth et al. ( 2024 ) Microsoft HoloLens 2 OST O-A 3D Endoscopic surgery (Cranial) Patient N/S Negrao et al. (2024) Microsoft HoloLens OST W-A 2D Laparoscopic surgery Phantom N/S Tohi et al. ( 2024 ) Microsoft HoloLens 2 OST O-A 3D Laparoscopic surgery 1 patient N/S Zhang et al. ( 2025 ) Microsoft HoloLens 2 VST W-A 3D Endoscopic surgery (Thyroidectomy) 1 patient N/S Park et al. ( 2025 ) Apple Vision Pro VST W-A 2D Endoscopic surgery (Spine) 1 patient “No perceptible lag” Broderick et al. ( 2025 ) Apple Vision Pro VST W-A 2D Laparoscopic surgeries (Various) 41 patients “No perceived latency” HMD: head-mounted display, OST: optical see-through, VST: video see-through, H-A: head-anchored, W-A: world-anchored, O-A: object-anchored, N/S: not specified. Across the included studies, a variety of commercial head-mounted displays (HMDs) have been adapted for endoscopic visualization and intraoperative guidance. The temporal relationship between device availability and research publication is summarized in Fig. 4 and Table 5 , highlighting a consistent lag between hardware release and academic adoption across different platforms. Early efforts were relied on industrial-grade HMDs such as the Sony HMS-3000MT (2013) and ODG R-7 (2016), as well as pre-consumer developer prototype such as the Oculus Rift Development Kit 2 (2014), which allows attaching custom module such as camera. The limited display resolution and narrow field of view of these early systems imposed clear constraints on their integration into endoscopic workflows, contributing to the notable delay between the first hardware releases and the first reported studies, as illustrated in Fig. 4 . Nevertheless, these pioneering investigations demonstrated the technical feasibility of using augmented visual overlays to support surgical orientation and intraoperative decision-making. Research activity increased markedly following the release of the Microsoft HoloLens (2016) and its successor HoloLens 2 (2019), both of which offered improved spatial tracking, open software development kits (SDKs), and sustained developer support from Microsoft. These platforms catalyzed a transition from proof-of-concept prototypes to clinically oriented research involving real patients and cadaveric validation. More recent studies have extended to emerging VST-type HMD systems such as the Apple Vision Pro , reflecting a trend toward higher-resolution displays, wider fields of view, and enhanced interaction through hand or gaze tracking. To account for the highly variable number of studies per device, the median time interval between device release and study publication was calculated in Table 5 as an indicator of research adoption speed—representing the typical translational latency within each HMD ecosystem. Notably, the Apple Vision Pro showed two endoscopy-related studies published recently within one year of its release, underscoring the accelerating pace of clinical adoption. Table 5 Head-Mounted Displays (HMDs) and Corresponding Research Publications in Endoscopic Applications. Release Year HMD Correlated Studies Study Count Minimum Interval (yrs) Median Interval (yrs) 2013 Sony HMS-3000MT Shen et al. ( 2020 ) 1 7 7 2014 Oculus Rift Development Kit 2 (with custom camara module for VST feature) Jayender et al. ( 2018 ) 1 4 4 2016 Microsoft HoloLens Carbone et al. ( 2018 ); Qian, L. et al. ( 2018 ); Huber et al. ( 2019 ); Jiang et al. ( 2019 ); Li et al. ( 2019 ); Lohou et al. ( 2019 ); Qian, L. et al. ( 2019 ); Al Janabi et al. ( 2020 ); Qian, L. et al. ( 2020 ); Ivan et al. ( 2021 ); Liu et al. ( 2021 ); Ma et al. ( 2022 ); Mak et al. (2022); Stewart et al. ( 2022 ); Zhang et al. ( 2022 ); Fu et al. ( 2023 ); Peng et al. ( 2023 ); Negrao et al. (2024) 18 2 4.5 2016 ODG R-7 Qian M. et al. ( 2019 ) 1 3 3 2017 Sony HMZ-T1 Xu et al. ( 2018 ) 1 1 1 2018 Epson Moverio BT-35E Okachi et al. ( 2022 ) 1 4 4 2019 MAD Gaze GLOW Plus Fang et al. ( 2023 ) 1 4 4 2019 Microsoft HoloLens 2 West et al. ( 2021 ); Arpaia et al. ( 2022 ); Khan et al. ( 2022 ); Song et al. ( 2022 ); Torabinia et al. ( 2022 ); Kildahl-Andersen et al. ( 2023 ); Acar et al. ( 2024 ); Forseth et al. ( 2024 ); Tohi et al. ( 2024 ); Zhang et al. ( 2025 ) 10 2 3.5 2024 Apple Vision Pro Broderick et al. ( 2025 ); Park et al. ( 2025 ) 2 1 1 In addition to the temporal and device-specific patterns summarized above, the extracted data also reveal how visualization design varies according to AR registration strategies implemented on HMD devices. As shown in Fig. 5 , the choice among head-anchored (H-A), world-anchored (W-A), and object-anchored (O-A) registration is closely associated with whether information is presented in two or three dimensions. H-A configurations were predominantly combined with 2D overlays, reflecting their use for continuously visible intraoperative information—such as vital signs or navigation cues—at a fixed position within the headset’s field of view. In contrast, W-A and O-A systems more often appeared with 3D visualizations, where reconstructed anatomical or imaging data are spatially registered within the operative scene. These patterns indicate distinct pairing preferences between registration strategy and image dimension, suggesting that spatial anchoring and visual complexity are jointly configured to meet specific informational and ergonomic requirements in endoscopic procedures. As illustrated in Fig. 6 , the same registration strategies also show distinct alignments with different endoscopic applications, reflecting how spatial anchoring is adapted to procedural demands. H-A systems are used across all application categories, underscoring the general value of readily available, fixed-position information; they are particularly common in transluminal and endoluminal procedures, where a stable visual reference aids navigation along extended luminal pathways. W-A configurations represent the most frequently adopted setup overall and dominate in general endoscopic as well as laparoscopic and thoracoscopic surgeries, where overlays fixed to the surrounding environment enhance depth perception and spatial orientation within anatomical cavities. O-A systems are the second most common approach, applied across all procedure types; by linking digital content to patient- or phantom-specific landmarks, they enable localized and high-precision guidance in complex regions. Collectively, these descriptive patterns constitute a frequency-based synthesis of how AR registration methods are applied across the reviewed studies. They demonstrate the progressive adaptation of AR-HMDs from general visualization support toward context-specific augmentation, providing a conceptual foundation for the detailed analyses of individual procedural domains presented in Sections 3.1 – 3.3 . 3.1. General Endoscopic Surgery General endoscopic surgery relies on precision and spatial awareness within confined anatomical cavities (Fig. 1 (a) ). AR-HMDs enhance visualization by overlaying critical anatomical information, such as neural pathways or vascular structures, onto the patient’s anatomy in real-time. This improves navigation, tool positioning, and workflow efficiency, reducing risks to vital structures and enhancing surgical precision. AR-HMDs have been shown to substantially enhance spatial perception and navigational precision in general endoscopic and neurosurgical procedures through 3D visualization and dynamic model integration. Even early-generation headsets, such as the Sony HMZ-T1 , provided a convenient means of displaying preoperative 3D reconstructions within the surgeon’s view, improving situational awareness even without real-time anatomical registration (Xu et al., 2018 ). Subsequent studies advanced this concept by superimposing 3D models onto the operative field using the Microsoft HoloLens , which improved depth perception and accuracy during complex navigation tasks (Carbone et al., 2018 ; Li et al., 2019 ; Liu et al., 2021 ). More recently, the HoloLens 2 has enabled real-time adjustment of AR models to maintain alignment with intraoperative changes (Forseth et al., 2024 ). A hybrid setup incorporating both 2D and 3D overlays allowed seamless switching between visual modes in the operating room (Ivan et al., 2021 ), representing an ideal application of AR-HMDs for flexible, spatially coherent guidance in incision planning and tumor-border identification. Confined surgical spaces in joint and arthroscopic surgeries demand a high degree of precision and ergonomic efficiency, making it ideal for the integration of HMD. Appling AR overlays on HoloLens in transforaminal percutaneous endoscopic discectomy not only streamlined surgical navigation but also reduced radiation exposure from conventional fluoroscopy (Liu et al., 2021 ). Similarly, while assessing the feasibility of MAD Gaze GLOW Plus , a lightweight OST-type HMD, in knee arthroscopy on phantom models, AR visual guidance was confirmed to offer ergonomic improvements (Fang et al., 2023 ). HoloLens 2 was applied to impose O-A AR overlay in hip arthroscopy, demonstrating an significantly increased alignment speed, improved positioning accuracy, and reduced mental effort comparing to baseline positioning without such AR assistance (Song et al., 2022 ), which contributes to efficiency in arthroscopic procedures. Applying HMDs in endoscopy also addresses the ergonomic and visual inefficiencies of traditional surgical displays. A cadaver study demonstrated the feasibility of using HoloLens 2 as an alternative to conventional screens for displaying 2D information, which reduced the operating room footprint while enhancing ergonomics (Khan et al., 2022 ). Although holographic feeds provided adequate coloration and resolution, tactile-visual asynchrony was identified as an area requiring refinement. Similarly, another study explored the use of a HoloLens 2 for displaying 3D hologram in endoscopic neurosurgery (Zhang et al., 2025 ), in which manual alignment of hologram to patient anatomy offered intuitive spatial cues for lesion localization and reduced the need for frequent reference to external navigation screens. These developments underscore AR’s ability to improve surgical ergonomics and efficiency, regardless of 2D or 3D content. Although the majority of studies in the review uses OST-type HMDs, recent evidence highlights the clinical feasibility of VST-type HMDs in endoscopic surgery by integrating multimodal data in an ergonomic AR interface in high resolution. Park et al. conducted the first published intraoperative study using the Apple Vision Pro during an actual endoscopic procedure (Park et al., 2025 ). In this setup, the endoscopic video feed, preoperative MRI models, and patient vital data were integrated as a W-A AR layer positioned above the surgical field, allowing the surgeon to access all visual information simultaneously without diverting attention to an external monitor. This configuration improved workflow efficiency and safety. To date, the Apple Vision Pro represents the first commercially available, consumer-grade VST-type HMD applied in endoscopic surgery. Although latency is often a concern with passthrough video systems, the study reported no perceptible lag when projecting a 4K endoscopic video feed onto a scalable virtual window, indicating that high-resolution VST-HMDs may offer clinically viable image quality and interaction fluidity for minimally invasive procedures. AR-HMDs have also shown utility in extending surgical skills through telemedicine. Microsoft HoloLens was used in a study for remote assistance in cranial neurosurgery, demonstrating a faster 5G network significantly improved real-time interaction compared to 4G, making remote guidance feasible and efficient (Zhang et al., 2022 ). This is the only article included in this review that focuses on using AR-HMD beyond the geographical barriers of the operating room. Furthermore, AR-guided instructions can accelerate trainee learning curves, showing the utility of AR in both surgical education and practice (Peng et al., 2023 ). Collectively, current evidence demonstrate the versatility of AR-HMDs in general endoscopic surgery, where they enhance spatial awareness, improve real-time visualization, and alleviate ergonomic limitations within confined operative fields. Across diverse contexts—from neurosurgical navigation to arthroscopic precision and telemedical collaboration—HMDs have demonstrated the capacity to streamline surgical workflows and support more intuitive, context-aware decision-making. These findings position AR-HMDs as a promising adjunct technology for advancing accuracy, efficiency, and connectivity in minimally invasive surgery. 3.2. Laparoscopic and Thoracoscopic Surgery Unlike flexible endoscopic procedures, laparoscopic and thoracoscopic surgeries are performed within insufflated abdominal, thoracic, or pelvic cavities, where limited depth perception from 2D endoscopic systems and the restricted view of traditional rigid-rod scopes present major spatial challenges (Fig. 1 b). The longer duration and greater complexity of these operations also increase ergonomic strain on the operator. In this setting, HMDs offer potential advantages by providing in-situ visualization as AR guidance, making them a promising adjunct to conventional monitors. In simulated laparoscopic and thoracoscopic surgery, AR-HMDs can provide real-time augmented guidance to mitigate the spatial and ergonomic limitations of traditional laparoscopic visualization and facilitate more intuitive surgical navigation. Microsoft HoloLens has been a popular choice in several studies. For instance, it was applied in simulated laparoscopic surgeries with an O-A 2D setup, which allows surgeons to view patient vitals and surgical imagery within their direct line of sight, minimizing head movement and enabling seamless transitions between tasks (Fu et al., 2023 ). These capabilities were also extended toward O-A 3D overlays aligned with patient-specific anatomy, enabling surgeons to visualize reconstructed structures directly on the operative field and thereby improve spatial awareness and targeting accuracy (Ma et al., 2022 ). A sequence of studies by Qian and colleagues demonstrated the feasibility and progressive refinement of AR-HMD integration into laparoscopic surgery in simulated settings. Using HoloLens , the researchers successively developed O-A 3D guidance systems that registered intra-abdominal anatomy and laparoscopic instruments in real time (Qian et al., 2018 ; L. Qian et al., 2019 ). Their work showed that spatially aligned 3D visualization improved depth perception, hand–eye coordination, and intraoperative orientation compared with conventional 2D displays. When extended to control of a flexible endoscope, the AR-HMD interface further enhanced operative efficiency and accuracy while reducing task workload in simulated procedures (Qian et al., 2020 ). Beyond simulation studies, AR-HMDs can bridge preoperative planning and intraoperative execution by improving spatial referencing, ergonomics, and depth perception in minimally invasive surgery. Several investigations have explored the translational potential of AR-HMDs in laparoscopic and thoracoscopic settings. Early pre-clinical work demonstrated the feasibility of using W-A 3D overlays on the HoloLens to guide trocar insertion in thoracoscopy, showing that spatially registered holographic visualization could improve orientation and reduce the risk of injury to underlying structures (Lohou et al., 2019 ). Complementary studies evaluated W-A 2D displays for simulated intraoperative use, confirming that HoloLens 2 could present vital signs and imaging data at fixed, ergonomically convenient locations with minimal latency (Arpaia et al., 2022 ). Subsequently, a clinical case report illustrated the integration of mixed reality guidance in laparoscopic retroperitoneal tumor resection, where HoloLens 2 facilitated port-site planning and intraoperative localization of a small lesion, enhancing precision and reducing unnecessary exposure (Tohi et al., 2024 ). Emerging evidence also supports the feasibility of VST-type HMDs for laparoscopic surgery, highlighting their potential as an alternative to traditional monitors through an immersive, high-resolution interface. Most recently, Broderick et al. reported the first published clinical use of the Apple Vision Pro in laparoscopic and hybrid minimally invasive procedures (Broderick et al., 2025 ). The study demonstrated that this VST-type HMD could operate as a stand-alone surgical monitor, simultaneously displaying multiple W-A 2D video feeds in 4 K resolution with no perceived latency . The system achieved low mental workload on NASA-TLX scores and provided ergonomic flexibility, allowing surgeons to position virtual displays freely within the operating room. Together with the earlier study by Park et al. ( 2025 ), this work establishes the first clinical evidence that a VST-type HMD such as the Apple Vision Pro can consolidate video and vital-sign data from multiple fixed monitors into an ergonomically optimized 3D workspace, improving spatial organization and workflow efficiency during endoscopic procedures. Benefiting from the immersive visual presentation of AR-HMDs, they can also ease training and skill acquisition for laparoscopic surgery. When applied in laparoscopic training, AR-HMD systems provides user with flexible viewing angle based on image from the fixed laparoscopic camera (Jiang et al., 2019 ), accelerate skill acquisition and reduce cognitive load for novice surgeons (Jayender et al., 2018 ; Stewart et al., 2022 ), reduce error rates and improved task accuracy laparoscopic suturing through 3D visualization (Shen et al., 2020 ), and offer utility in training scenarios and complex surgical tasks such as oncology and liver surgeries (Negrao & Maciel, 2024 ; Torabinia et al., 2022 ). All these studies prove that AR-HMDs can provide efficient, intuitive training experience to improve accuracy of endoscopic skills. Collectively, current evidence indicates that AR-HMDs enhance depth perception and spatial awareness, thereby improving tool positioning and navigation accuracy within confined cavities. Real-time augmented guidance has been shown to facilitate complex surgical maneuvers and reduce cognitive and visual workload, particularly in lengthy laparoscopic procedures. Beyond intraoperative benefits, the immersive and context-rich visualization offered by AR-HMDs also holds promise for improving training efficiency and accelerating skill acquisition in minimally invasive surgery. 3.3. Transluminal and Endoluminal Surgery Transluminal and endoluminal surgery requires navigating endoscopes through narrow anatomical pathways, such as the airway or gastrointestinal tract. In bronchoscopy where a flexible endoscope is used, maneuvering the scope in complex airway lumen space requires with limited visibility that limits the surgeon’s spatial awareness (Fig. 1 (c) ). AR-HMDs have emerged as innovative tools to address these challenges. AR-HMDs have shown considerable educational value in transluminal and endoluminal procedures by enabling immersive, hands-free visualization and real-time instructor interaction. In one airway training study using the early ODG R-7 optical see-through headset, the live laryngoscopic camera feed was projected directly into the trainee’s visual field, allowing learners to maintain a natural line of sight with the phantom airway while simultaneously viewing an enhanced glottic image in an scalable window, although the headset’s limited field of view constrained flexibility of adjustment (M. Qian et al., 2019 ). The addition of telestration and shared instructor perspectives further improved intubation performance and enabled real-time supervision. Overall, the study demonstrated that AR-HMDs can serve as effective educational platforms for airway management, accelerating skill acquisition and improving performance across experience levels. HMDs have also been explored as AR-based navigation platforms for transluminal and endoluminal interventions, integrating multimodal imaging data to enhance spatial awareness and procedural precision. Early applications primarily focused on endovascular navigation. In a representative preclinical study, West et al. ( 2021 ) employed the Microsoft HoloLens 2 during an aortic intervention in a porcine model, registering a three-dimensional CT reconstruction of the aorta to fiducial markers placed on the animal’s ventral surface (West et al., 2021 ). This study was the only one in the current review utilizing a 3D overlay rather than conventional 2D visualization. The O-A holographic alignment allowed operators to correlate the catheter’s position with vascular anatomy in real time, thereby improving spatial orientation and overall procedural awareness within the vascular lumen. In bronchoscopy, the intraluminal view provides essential spatial cues for navigating the flexible endoscope through the complex airway, and AR-HMDs offer an ergonomically convenient way to display these views as augmented overlays within the operator’s field of vision. Some studies utilized head-anchored visualization of HMD to place the AR views at a fixed position within the field of view. For example, the Epson Moverio BT-35E , an OST-type HMD, was applied in bronchoscopic navigation to present live endoscopic video, virtual bronchoscopic video, and fluoroscopic images simultaneously in the operator’s field of view (Okachi et al., 2022 ). Although the HMD functions as a display-only headset without environment tracking—therefore providing only a head-anchored overlay—it enabled bronchoscopists to access multimodal imaging data directly within their line of sight, minimizing head movement and reliance on external monitors. In comparison, Microsoft HoloLens 2 has more advanced OST capabilities, and was later evaluated for electromagnetic-guided bronchoscopy in a lung-phantom model, which successfully supported navigation to distal bronchi (Kildahl-Andersen et al., 2023 ). These implementations of OST-type HMDs demonstrated that real-time AR can effectively assist transluminal navigation despite persistent limitations in image resolution and color fidelity—even with newer devices such as the HoloLens 2. Beyond bronchoscopic and vascular navigation, AR-HMDs have also been applied across diverse endoluminal procedures to improve operator performance and ergonomics. In rectoscopy, where a rigid endoscope provides direct visualization of the rectum and distal sigmoid colon, overlaying intraoperative video onto HoloLens worn by surgeons, assistants, and trainees enhanced spatial awareness and ergonomic posture across the team. The system reduced perceived task load per NASA-TLX assessments, although residual latency and limited display resolution remained notable technical constraints (Huber et al., 2019 ). While in ureteroscopy, a study conducted the first prospective comparative study assessing the HoloLens as an AR display for ureteroscopy simulation (Al Janabi et al., 2020 ). Across 72 participants of varying experience, use of the HMD significantly reduced procedural time and increased performance scores, while 95% of users rated it feasible for clinical practice and 97% endorsed its educational value. Participants also reported improved ergonomics and spatial alignment relative to conventional monitors. Building on this, integration of preoperative 3-D imaging with real-time endoscopic views through a mixed-reality HoloLens 2 interface enhanced stone localization accuracy, increased eye fixation time, and also reduced task load on NASA-TLX assessments, while shared gaze visualization facilitated team coordination during navigation (Acar et al., 2024 ). Collectively, these studies confirm that AR-HMDs extend beyond navigation to enhance procedural precision, ergonomic safety, and educational effectiveness across a wide spectrum of transluminal and endoluminal interventions. Collectively, current evidence indicates that AR-HMDs provide tangible benefits in transluminal and endoluminal surgery by addressing the fundamental challenges of navigating narrow and tortuous luminal pathways. By integrating multimodal imaging and projecting real-time visual information directly within the operator’s field of view, these systems enhance spatial awareness, facilitate smoother endoscope manipulation, and reduce dependence on external monitors. Such context-aware visualization is particularly advantageous in airway navigation and other confined luminal procedures, where maintaining continuous orientation and ergonomic efficiency is critical. 4. Discussion Building upon the findings presented in the previous sections, this discussion analyzes the advantages and limitations of integrating AR-HMDs across different types of endoscopic procedures and outlines future directions for refining HMD technology to better meet clinical requirements. The comparative performance of the six evaluated configurations—H-A 2D, H-A 3D, W-A 2D, W-A 3D, O-A 2D, O-A 3D—is summarized in Table 6 and visualized in Fig. 7 . These ratings were derived from the predefined evaluation framework described in Section 2.5 and were independently assessed by both authors based on the synthesized evidence from the included studies. Any discrepancies in the initial ratings were resolved through iterative discussion until a consensus was achieved for each evaluation aspect, ensuring the internal consistency and interpretive rigor of the final results. The six evaluation aspects— Visibility , Ease of Setup , Ease of Use , Cognitive Efficiency , Latency , and Adaptability —were scored on a five-point Likert scale (1 = Not usable, 2 = Hardly acceptable, 3 = Acceptable, 4 = Good, 5 = Excellent), where a score of 3 represents performance comparable to that of a conventional monitor. This approach provides a qualitative yet structured basis for comparing HMD-based configurations with traditional display systems. Table 6 Rating for the Performance of HMDs in Endoscopy. Aspect H-A 2D H-A 3D W-A 2D W-A 3D O-A 2D O-A 3D (Aspect Average) Visibility 5 5 4 4 5 5 4.67 Ease of Setup 5 5 4 4 3 3 4 Ease of Use 4 4 4 4 5 5 4.33 Cognitive Efficiency 3 4 4 5 4 5 4.16 Latency 5 4 4 3 4 3 3.83 Adaptability 4 5 4 5 4 5 4.5 (Configuration Average) 4.33 4.5 4 4.16 4.16 4.33 4.25 Visibility : Refers to the extent to which critical information stays consistently accessible and clearly visible during the procedure. Ease of Setup : Evaluates the complexity and effort needed to calibrate and prepare the system for use, including hardware and software adjustments. Ease of Use : Reflects the simplicity and efficiency with which users can operate the system accurately during procedures, minimizing physical strain. Cognitive Efficiency : Measures how effectively the system presents information in a clear, interpretable, and intuitive manner, reducing cognitive load for grasping the information. Latency : Assesses the delay between input data and its display on the HMD, with lower latency indicating better real-time responsiveness. Adaptability : Indicates the system's flexibility and usability to accommodate various endoscopic procedures and scenarios. These results underscore that each AR registration strategy reflects a distinct trade-off among immediacy, spatial precision, and system complexity, rather than a simple hierarchy of performance. According to these assessments, the comparative configuration averages reveal distinct performance tendencies among different AR-HMD setups. H-A systems achieved the highest configuration average (≈ 4.42), highlighting their strengths in ease of setup and low latency . Their straightforward alignment with the surgeon’s direct line of sight enables efficient visualization and rapid data access during time-sensitive procedures. In contrast, the spatial anchoring of O-A and W-A systems provides a more integrated anatomical perspective, supporting immersive visualization at the expense of increased calibration demands. O-A systems, averaging approximately 4.25, excel in ease of use and deliver the most intuitive visualization by attaching holographic data to patient- or phantom-specific landmarks, yet they are also the most complex to configure. W-A systems, with a slightly lower mean of ≈ 4.08, represent a balanced compromise between immediacy and spatial fidelity—offering cognitive efficiency and adaptability comparable to O-A setups while requiring less extensive calibration. The aspect-level patterns depict a maturing yet still evolving technological landscape. When analyzed by evaluation aspect, the aggregated results (overall mean = 4.25, “Good”) indicate that AR-HMDs consistently outperform conventional monitors across multiple usability domains. Visibility (4.67) and adaptability (4.50) received the highest ratings, underscoring the clear presentation of critical information and flexibility of application across diverse procedural contexts. Ease of use (4.33) and cognitive efficiency (4.17) were also rated positively, reflecting improved user interaction and reduced mental workload through intuitive data visualization. In contrast, ease of setup (4.00) and latency (3.83) emerged as relative weaknesses, illustrating that technical preparation and real-time responsiveness remain key barriers to seamless clinical adoption. Taken together, these comparative results establish a structured foundation for the subsequent analysis of advantages (Section 4.1 ) and limitations (Section 4.2 ), elucidating how different AR-HMD configurations can be further optimized to enhance usability, spatial cognition, and workflow integration in endoscopic surgery. 4.1. Advantages The integration of HMDs into endoscopic procedure offers distinct advantages that mitigate long-standing ergonomic and perceptual challenges. These advantages—enhanced visibility, improved ease of use, increased cognitive efficiency, and adaptability to different procedural demands—collectively contribute to a more seamless and intuitive surgical workflow. 4.1.1. Enhanced Visibility and Spatial Awareness AR-HMDs enhance surgical visibility and spatial awareness by integrating augmented information directly into the surgeon’s field of view. In conventional endoscopic procedures, surgeons must frequently shift their line of sight between the operative field and external monitors to acquire critical data, disrupting workflow and reducing situational awareness (Johnson et al., 2022 ). H-A configurations resolve this issue by keeping essential information consistently aligned with the surgeon’s gaze, ensuring uninterrupted access to visual cues. W-A systems stabilize data spatially within the operating environment, providing a broader contextual view that improves orientation during complex maneuvers. O-A systems further refine visibility by projecting holographic 3D overlays directly onto anatomical structures in real time (L. Qian et al., 2019 ) (Ivan et al., 2021 ), allowing intuitive, anatomy-referenced visualization that supports precise tool navigation. 4.1.2. Improved Ease of Use By consolidating multiple visual and control interfaces into a single immersive platform, HMDs streamline endoscopic workflows and reduce operator fatigue. In traditional setups, surgeons must rely on several external monitors and input devices, resulting in cumulative neck and eye strain during lengthy or complex procedures (Johnson et al., 2022 ). Once the visual overlay is configured prior to surgery, HMDs enable hands-free or minimally interactive control—such as eye-tracking and gesture-based commands—allowing smoother task execution with reduced physical effort. H-A systems keep critical data within the surgeon’s natural line of sight, eliminating repetitive head movements. W-A and O-A configurations position 2D or 3D visualizations spatially close to the operative field or directly onto anatomical structures, thereby reducing the disruption caused by consulting external displays (Lin et al., 2019 ). In addition, integrating AR visualization into the surgical workflow helps maintain focus on the operative field and alleviates physical fatigue, particularly during prolonged procedures (Fang et al., 2023 ). 4.1.3. Improved Cognitive Efficiency Integrating augmented reality into HMDs enhances cognitive efficiency by reducing the mental effort required to process dispersed information during endoscopic procedures. In traditional workflows, surgeons must mentally consolidate data from multiple sources—such as preoperative imaging, intraoperative sensors, and real-time endoscopic visuals—which increases cognitive load and slows decision-making. AR-HMDs address this challenge through centralized visualization platforms that overlay key information, including anatomical landmarks, tool trajectories, and sensor feedback, directly within the surgeon’s field of view (Al Janabi et al., 2020 ; Fu et al., 2023 ; Kildahl-Andersen et al., 2023 ). By presenting these data streams simultaneously in a unified and interpretable format, the systems enable seamless integration of multimodal information and reduce the interruptions inherent to conventional monitor-based setups. 4.1.4. Workflow Adaptability and Training Benefits AR-HMDs enhance surgical adaptability and training efficiency by extending visualization and collaboration beyond conventional operating settings. Their immersive and spatially flexible displays allow remote guidance and real-time teleassistance: the Microsoft HoloLens enabled effective remote support in cranial neurosurgery, with 5G connectivity providing smooth interaction compared to 4G networks (Zhang et al., 2025 ). In training contexts, AR-HMDs facilitate intuitive, hands-free learning through immersive 3D visualization. Studies in laparoscopic simulation demonstrated improved task accuracy, faster skill acquisition, and reduced cognitive load for novice surgeons (Jayender et al., 2018 ; Jiang et al., 2019 ; Shen et al., 2020 ; Stewart et al., 2022 ). Similarly, AR-guided laryngoscopic training using the ODG R-7 improved intubation performance through shared instructor views and telestration (M. Qian et al., 2019 ). By integrating augmented visualization, intuitive control, and adaptive display design, AR-HMDs create a unified platform that enhances visibility, usability, and cognitive performance during endoscopic procedures. These systems enable surgeons to access and interact with critical information directly within their field of view, maintaining workflow continuity while reducing physical and mental strain. Collectively, these advantages establish AR-HMDs as effective tools for improving precision, efficiency, and situational awareness in minimally invasive surgery. 4.2. Limitations Despite the advantages discussed above, large-scale adoption of AR-HMDs in endoscopy remains constrained by several critical limitations. The most pressing challenges include excessive latency in real-time data processing, ergonomic discomfort during prolonged use, and the technical complexity of workflow setup—particularly in achieving stable and accurate 3D image registration. These limitations not only restrict current clinical deployment but also highlight the need for coordinated improvements in hardware design, system optimization, and human–machine integration to ensure sustainable clinical usability. 4.2.1. System Performance Constraints The most critical technical limitation of current AR-HMDs in endoscopy lies in system latency and its impact on visual accuracy and user comfort. Latency—the delay between image capture and display—remains substantially higher than the perceptual threshold required for real-time feedback, often exceeding 300 ms in 3D-capable HMD systems (Kildahl-Andersen et al., 2023 ; L. Qian et al., 2019 ). Such delays can cause misalignment between virtual and physical objects, leading to visual fatigue or motion sickness (Andrievskaia et al., 2023 ; Kundu et al., 2021 ; Park et al., 2022 ). This issue is particularly detrimental in high-precision procedures such as neurosurgery, where even millisecond-level discrepancies may compromise spatial accuracy and increase surgical risk. Studies have shown that maintaining latency below approximately 20 ms can effectively prevent these effects (Kundu et al., 2021 ), a benchmark far from what current systems achieve. Multiple review studies have reached similar conclusions, emphasizing latency reduction as a prerequisite for achieving stable and comfortable AR experiences (Anua et al., 2022 ; Stauffert et al., 2020 ). Efforts to address latency depend on improvements in both hardware—including faster GPUs, optimized rendering pipelines, and low-latency transmission—and software, such as adaptive algorithms for real-time tracking and image registration. While Moore’s law no longer progresses exponentially (Moore, 1998 ), innovations in 3D transistor design, advanced lithography, and high-bandwidth communication (e.g., 5G and 6G uRLLC) may enable future reductions in latency (Burg & Ausubel, 2021 ; Kumari et al., 2024 ). Continued advances in these domains are essential to achieving the sub-20 ms performance required for fatigue-free, clinically reliable AR-HMD operation. 4.2.2. Ergonomic Limitations Despite improving intraoperative visibility, current AR-HMDs impose notable ergonomic limitations that hinder their sustained clinical use. Although HMDs can reduce the need for head movement, they often introduce new comfort issues—particularly during prolonged procedures (Fu et al., 2023 ). VST-type HMDs such as the Oculus Rift and Apple Vision Pro are bulkier and heavier because of integrated processors and cameras for higher performance (Broderick et al., 2025 ; Jayender et al., 2018 ; Park et al., 2025 ). Studies have shown that while short-term fatigue is minimal, poor weight distribution can cause neck discomfort and visual strain over longer use (Ito et al., 2021 ). The widely adopted Microsoft HoloLens , released in 2016 and used in half of the reviewed studies, also suffers from a limited field of view (34°), constraining the visibility and the amount of information that can be presented within the overlay (Al Janabi et al., 2020 ). Different fixation mechanisms—ear hooks, headbands, and overhead straps—have been explored to mitigate these effects. Headbands are often difficult to adjust effectively (Al Janabi et al., 2020 ),, whereas overhead straps distribute weight more evenly across the head, improving comfort during extended use, especially with heavier HMDs (Qian et al., 2017 ). To make AR-HMDs more practical for endoscopic applications, especially in lengthy laparoscopic procedures, future designs must prioritize lighter materials, better weight balance, and adjustable ergonomics to accommodate diverse clinical users and settings. 4.2.3. Workflow and Setup Challenges Another key limitation of AR-HMDs lies in the complexity of workflow setup, particularly in achieving accurate image registration for 3D visualization. For world-anchored and object-anchored systems reviewed in this study, registration between virtual models and the patient’s anatomy remains the most technically demanding step before clinical use. Integrating multimodal imaging—such as CT, MRI, and real-time endoscopic data—requires precise spatial alignment, which is often manual and highly operator dependent. Among the reviewed systems, only one employed combined fiducial and simultaneous localization and mapping (SLAM) tracking to partially automate this process (L. Qian et al., 2019 ); all others relied on manual initial registration and subsequent re-registration to compensate for tracking drift during procedures (Ivan et al., 2021 ; Qian et al., 2018 ; L. Qian et al., 2019 ; Suter et al., 2023 ). This dependency on manual calibration not only prolongs setup time but also increases the risk of misalignment as the surgical field changes. Overall, the need for repeated manual registration continues to constrain workflow efficiency, underscoring that improved tracking stability and user-friendly calibration protocols are essential for broader clinical translation of AR-HMD systems. Overall, the limitations outlined in this section highlight the key technical and practical barriers that must be overcome for AR-HMDs to achieve reliable clinical integration. Addressing these challenges requires a comprehensive approach that advances both technology and usability. Reducing latency through faster rendering pipelines and high-bandwidth transmission will be essential for achieving stable, fatigue-free visualization. Ergonomic refinements—including lighter materials and better weight distribution—will enhance comfort and make prolonged use more practical. Finally, progress in automatic registration methods such as SLAM and real-time image processing is expected to replace manual calibration and fiducial-based alignment (Marchesi et al., 2021 ; Reimer et al., 2021 ; Sun et al., 2024 ), streamlining setup and improving workflow efficiency. Collectively, these developments will determine whether AR-HMDs can transition from experimental feasibility to reliable clinical adoption. 5. Conclusion This scoping review synthesized 36 studies published over the past decade on the application of augmented reality head-mounted displays (AR-HMDs) in different categories of endoscopic procedures. To organize and compare findings across heterogeneous systems, a structured qualitative framework based on a customized Likert-scale assessment was applied. This approach provided a consistent basis for summarizing user- and system-centered characteristics where quantitative indicators were unavailable, enabling a more coherent interpretation of existing evidence. Several methodological constraints should be acknowledged. Research in this domain remains in an early stage, with limited sample sizes and inconsistent reporting of key performance parameters such as latency. The qualitative rating method, although structured, introduces subjectivity, as only two reviewers participated and inter-rater reliability was not formally tested. In addition, variability in system design within each configuration type may have contributed to inconsistent findings, limiting the ability to establish definitive best practices for specific clinical contexts. Overall, the synthesized evidence indicates that AR-HMDs can enhance surgical visibility, usability, and cognitive efficiency while also supporting emerging applications in telemedicine and immersive training. Nevertheless, widespread clinical adoption remains constrained by challenges related to latency, ergonomics, and workflow complexity. Continued progress will depend on collaborative efforts among engineers, clinicians, and regulators to improve technical performance, usability, and standardization. As these technologies mature, AR-HMDs are expected to become more seamlessly integrated into modern endoscopic practice. Declarations Acknowledgements Not applicable. Author Contributions Mingwei Cui: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review and editing. Xiaorong Gao: Conceptualization, Funding Acquisition, Project administration, Resources, Supervision, Writing – review and editing. Both authors agreed with the content and that they all gave explicit consent to submit and that they obtained consent from the responsible authorities at the institute/organization where the work has been carried out, before the work is submitted. Funding Open access funding provided by the National Natural Science Foundation of China (U2241208, 62171473, 61671424), the National Key Research and Development Program of China (2022YFC3602803, 2023YFF1205300), Key Research and Development Program of Ningxia (2023BEG02063). Competing interests The authors declare no competing interest. Ethical approval This paper is a scoping review of published studies, and since it does not involve primary data collection, there is no data to make available for public access. Similarly, as this paper is a review paper without involving human participants, no ethics approval or informed consent was necessary. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third-party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/. 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09:04:41","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":294659,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/279a92944bc6271dc1cc49e3.html"},{"id":96916738,"identity":"0f00b095-880c-4f75-ae3d-f2b7776949aa","added_by":"auto","created_at":"2025-11-27 14:08:51","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":359300,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eRepresentative operative scenes illustrating three categories of endoscopic procedures: (a) General Endoscopic Surgery, (b) Laparoscopic and Thoracoscopic Surgery, and (c) Transluminal and Endoluminal Procedure.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/1d1f530c5ebf6808b7049db1.jpeg"},{"id":96803988,"identity":"19766c23-1a33-4cff-99d1-eda86251516c","added_by":"auto","created_at":"2025-11-26 09:04:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":200279,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSchematic illustration of optical see-through (OST) and video see-through (VST) HMDs.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/1bae9f27f053ee509f081994.png"},{"id":96803987,"identity":"7c10d3d6-8bad-404d-a057-d16a16925411","added_by":"auto","created_at":"2025-11-26 09:04:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":27069,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePRISMA-ScR workflow diagram。\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e* The original identification included articles, clinical trials, comparative studies, meeting papers, case reports and reviews published between 2014 and 2025, while excluding letters, patents, grants, abstracts, book chapters, and theses.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e** Additional records (N = 5) were identified through reference scanning during the screening phase and subsequently included in the full-text eligibility assessment.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/e701c1c29972af0e8c4aef4e.png"},{"id":96916823,"identity":"e43b5675-0483-4607-9ee4-801d9a784198","added_by":"auto","created_at":"2025-11-27 14:08:56","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":185674,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAnnual number of head-mounted displays (orange) commercially released and academic studies (blue) published on AR-HMD applications in endoscopy between 2013 and 2025.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/fcb61af246807012f550f482.jpeg"},{"id":96803995,"identity":"818cceb4-e7b4-4623-881c-db56a327c090","added_by":"auto","created_at":"2025-11-26 09:04:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":104951,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eStudy count by display modality (2D and 3D) across AR registration methods (H-A, W-A, O-A).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/a5eb8a2b1cc801f33c22d83c.png"},{"id":96803998,"identity":"0d065ab3-6bab-4c9f-8ae8-a02d1d5be63e","added_by":"auto","created_at":"2025-11-26 09:04:41","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":150060,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eStudy count by endoscopic procedure type—general endoscopic, laparoscopic/thoracoscopic, and transluminal/endoluminal—across AR registration methods (H-A, W-A, O-A).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/c7af85c17fdc56cdc2b3f04b.png"},{"id":96917033,"identity":"a2a17672-db77-487b-94ce-3300d8279def","added_by":"auto","created_at":"2025-11-27 14:09:09","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":395167,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eComparative performance of AR-HMD configurations in endoscopy. (a) 2D HMD performance across six evaluation aspects—visibility, ease of setup, ease of use, cognitive efficiency, latency, and adaptability. (b) 3D HMD performance across the same aspects.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/34132ee5b9d7a764f15a5900.jpeg"},{"id":100357179,"identity":"b0291293-1e2d-4660-95c9-91221e173fff","added_by":"auto","created_at":"2026-01-16 07:19:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3237818,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/36957586-bac3-4889-a353-f6724c739d64.pdf"},{"id":96918268,"identity":"f82770da-1010-4736-83b9-42e53347bb0c","added_by":"auto","created_at":"2025-11-27 14:11:33","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":14463,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8098102/v1/2c3364ec5ebc998d052c6e15.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Current Perspectives on Augmented Reality and Head-Mounted Displays in Endoscopy: A Scoping Review","fulltext":[{"header":"1. Background","content":"\u003cp\u003eEndoscopy is a medical technique that enables internal visualization and access to organs and tissues through natural orifices or small incisions, allowing both diagnostic and interventional procedures without the need for open surgery. By avoiding the extensive tissue disruption characteristic of open surgery, endoscopic approaches substantially reduce patient trauma, recovery time, and hospitalization, contributing to improved clinical outcomes (Liawrungrueang et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Patil et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Qadrie et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Owing to these advantages, endoscopy has become an essential technique across diverse clinical domains, including gastrointestinal, respiratory, urological, and neurosurgical interventions (Jitpakdee et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn endoscopic procedures, the operative site is spatially separated from the visual feedback displayed on an external monitor (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e This indirect visualization requires surgeons to frequently alternate their gaze between the patient and the screen, disrupting natural hand\u0026ndash;eye coordination and increasing both cognitive and physical workload. Consequently, improving the immediacy and spatial integration of visual feedback has become a central focus for developing next-generation visualization technologies in endoscopy. As summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, endoscopic techniques can be broadly classified into three procedural categories\u0026mdash;general endoscopic surgery, laparoscopic and thoracoscopic surgery, and transluminal or endoluminal surgery\u0026mdash;based on their anatomical access routes and operative environments. General endoscopic surgery (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) involves rigid or semi-rigid scopes used within confined spaces such as the brain ventricles or joint cavities. Laparoscopic and thoracoscopic surgery (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) employs rigid rod-lens endoscopes inserted through small incisions to operate inside insufflated abdominal or thoracic cavities, representing the most established form of minimally invasive surgery (Marks, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Transluminal and endoluminal surgery (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec), in contrast, uses flexible scopes introduced through natural orifices to access internal lumens of organs such as the gastrointestinal or respiratory tracts (McCarty, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWithin this framework, augmented reality (AR) and head-mounted displays (HMDs) have been increasingly explored as potential interfaces to enhance spatial awareness, visual ergonomics, and procedural efficiency in endoscopic environments.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical and technical characteristics of three categories of endoscopic procedures.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAspect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGeneral Endoscopic Surgery\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLaparoscopic and Thoracoscopic Surgery\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTransluminal and Endoluminal Procedure\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEntry Route\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmall incision\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSmall incision (with trocar port for sealing gas)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNatural orifice (mouth, urethra, anus, etc.)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOperative Site\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConfined anatomical cavities (e.g., cranial ventricles, joints)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInsufflated abdominal, thoracic, or pelvic cavities,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNatural lumens (respiratory, gastrointestinal, or urinary tracts)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary Purpose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDiagnostic or localized therapeutic procedures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurgical interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDiagnostic and interventional procedures\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepresentative Use Cases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCranial neurosurgery, ventriculostomy, arthroscopy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThoracoscopy, cholecystectomy, appendectomy, hernia repairs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBronchoscopy, gastrointestinal polypectomy, ERCP, Ureteroscopy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEndoscope Type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRigid or semi-rigid endoscopes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRigid rod-lens endoscopes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFlexible or rigid fiber-optic endoscopes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAncillary Tools\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecialized endoscopic instruments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGraspers, dissectors, retractors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiopsy or ablation devices\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOperational Technique\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNavigation and manipulation of the endoscope within confined spaces\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHand-eye coordination to manipulate multiple rigid instruments, precise control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNavigation and control of scopes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComplexity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcedure Duration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModerate to long\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eShort to moderate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLearning Curve\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSteep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eERCP: Endoscopic Retrograde Cholangiopancreatography\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1. Categories of Head-Mounted Displays\u003c/h2\u003e\u003cp\u003eHead-mounted displays (HMDs) have been explored as an alternative to conventional surgical monitors for intraoperative visualization. By presenting critical visual information within the user\u0026rsquo;s direct line of sight, HMDs minimize the need for head and gaze shifts, improving ergonomic alignment and potentially reducing musculoskeletal strain during prolonged procedures (Doughty et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Johnson et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Maithel et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Qian et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHMDs can be categorized into two types according to their visualization mechanism: optical see-through (OST) and video see-through (VST) systems (Rolland et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. OST-type HMDs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) superimpose computer-generated imagery onto the user\u0026rsquo;s natural view through transparent or semi-transparent optical elements\u0026mdash;often holographic waveguides or related components (Hong et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This configuration preserves natural stereo vision and depth cues, offering intuitive situational awareness in clinical environments, but it is constrained by limited field of view (FOV), reduced display brightness, and diminished contrast of virtual elements due to optical projection.\u003c/p\u003e\u003cp\u003eBy contrast, VST-type HMDs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) use forward-facing cameras to capture the real environment and digitally combine it with virtual overlays on opaque displays. This architecture enables fine control over the degree of visual immersion and supports augmented reality (AR), mixed-reality (MR), virtual reality (VR) presentation along the reality\u0026ndash;virtuality continuum (Milgram \u0026amp; Kishino, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). VST systems typically provide higher-resolution virtual imagery and wider FOVs than OST devices, but their reliance on camera input introduces inherent latency and may reduce the fidelity of real-world visuals, depending on camera performance and on-device processing.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2. Value of HMDs for Endoscopic Procedures\u003c/h2\u003e\u003cp\u003eDuring endoscopic procedures, physicians manipulate surgical instruments through natural orifices or small incisions while relying on real-time endoscopic information\u0026mdash;including video streams of the operative site and the patient\u0026rsquo;s vital parameters\u0026mdash;for spatial orientation and decision-making. In contrast to conventional endoscopic monitors which are positioned at a distance from the operative field, HMDs\u0026mdash;including both OST and VST types\u0026mdash;present visual information directly within the user\u0026rsquo;s line of sight, naturally integrating virtual content with the surrounding environment and thereby improving workflow continuity.\u003c/p\u003e\u003cp\u003eEach category of HMD provides distinct advantages. OST-type HMDs project digital overlays onto transparent optics, allowing surgeons to maintain direct visual contact with the patient and operative field. This mechanism preserves natural depth perception and situational awareness with minimal obstruction, making it particularly useful in procedures where augmented content supports rather than dominates visual guidance. However, optical projection imposes physical limitations\u0026mdash;restricted field of view (FOV) and limited brightness\u0026mdash;that constrain the fidelity of rendered information. Alternatively, VST-type HMDs capture the surrounding environment via forward-facing cameras and digitally merge it with high-resolution virtual content on opaque displays. This configuration is advantageous for tasks emphasizing detailed visualization of the endoscopic scene, though the added computational load and device weight may contribute to operator fatigue during long procedures.\u003c/p\u003e\u003cp\u003eTo assess the technological readiness of these two categories for endoscopic use, representative AR HMDs were examined. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the key specifications of commercially available or investigational devices, including HMD type, processing power (processor and memory), display quality (display type, resolution, refresh rate, and FOV), software platform (OS), and form factor (weight and fixture). Presented chronologically, the table illustrates the steady evolution of HMD technology toward higher processing capabilities and improved visual performance\u0026mdash;developments that are critical for supporting real-time high-definition endoscopic video and ensuring system stability in image-intensive surgical environments.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTechnical specifications and chronological overview of augmented-reality head-mounted display (AR-HMD) devices.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear of Release\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDevice\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHMD type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProcessor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMemory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDisplay type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eResolution (per eye)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRefresh Rare\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eFOV (Diagonal)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eOS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eWearable weight\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eFixture\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSony HMZ-T1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A (video source needed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOLED\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1280 x 720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e45\u0026deg;\u003c/p\u003e\u003cp\u003e(horizontal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e420 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSony HMS-3000MT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A (video source needed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOLED\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1280 x 720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60 H\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e45\u0026deg;\u003c/p\u003e\u003cp\u003e(horizontal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e480g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eOverhead strap\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEpson Moverio BT-200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 x 1.2 GHz, TI OMAP 4460\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e960 x 540\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e23\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eAndroid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e88 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eEar hook\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eODG R-7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 x 2.7 GHz, Qualcomm Snapdragon 805\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCoS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1280 x 720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e100 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e30\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eReticleOS (Android)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e125 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eOverhead strap, ear hook\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 x 1.84 GHz, Intel Atom x5-Z8100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCoS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1268 x 720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e34\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eWindows Holographic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e579 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eOverhead strap\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBrother\u0026rsquo;s AiRScouter WD-200B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A (video source needed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1280 x 720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e17.8\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e145 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEpson Moverio BT-35E\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 x 2.5 GHz, 6 x 1.7 GHz, Qualcomm Snapdragon XR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1280 x 720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e30 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e30\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eAndroid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e119 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eOverhead strap\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSamsung Odyssey+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A (video source needed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAMOLED\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1600 \u0026times;1440\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e90 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e101\u0026deg;\u003c/p\u003e\u003cp\u003e(horizontal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSteamVR, Windows Mixed Reality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e590\u0026nbsp;g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMagic Leap 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNvidia Parker SoC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCoS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1280 x 960\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e122 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e50\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eLumin OS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e316g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOculus Quest V1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 x 2.45 GHz, 4 x 1.9 GHz, Qualcomm Snapdragon 835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOLED\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1600 \u0026times;1440\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e72 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e115\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eAndroid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e571 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4x 2.96 GHz, 4 x 1.8 GHz, Qualcomm Snapdragon 850\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLBS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1440 x 936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e52\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eWindows Holographic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e556 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValve index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A (PC-powered)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1600 \u0026times;1440\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e144 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e114\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e809 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMAD Gaze GLOW Plus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A (PC-powered)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOLED\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1920 x 1080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e60 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e45\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eAndroid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e92 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eRigid arms\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHTC Vive Pro 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A (PC-powered)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2448 x 2448\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e120 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e113\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e850g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMeta Quest 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 x 3.19 GHz, 4 x 2.8 GHz, 3 x 2.0 GHz, Qualcomm Snapdragon XR2 Gen 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2064 x 2208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e120 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e110\u0026deg; (horizontal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eAndroid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e515 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApple Vision Pro\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 x 3.5 GHz, 4 x 2.4 GHz, Apple M2\u0026thinsp;+\u0026thinsp;R1 chip\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMicro-OLED\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3660 x 3200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e100 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e~\u0026thinsp;100\u0026deg; (horizontal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003evisionOS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e650 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePico 4 ultra\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 x 3.19 GHz, 4 x 2.8 GHz, 3 x 2.0 GHz, Qualcomm Snapdragon XR2 Gen 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12 GB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLCD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2160 x 2160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e90 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e122\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003ePico OS (Android)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e580 g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHeadband\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eOST: optical see-through, VST: video see-through, FOV: fields of view, OS: operating system, OLED: Organic Light Emitting Diode, LCD: Liquid Crystal Display, LCoS: Liquid Crystal on Silicon, LBS: Laser Beam Scanning, PC: personal computer, N/S: not specified.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e1.3. Value of AR for Endoscopic Procedures\u003c/h2\u003e\u003cp\u003eBuilding on advances in medical imaging segmentation and three-dimensional (3D) reconstruction technologies, augmented reality (AR) provides an effective solution for enhancing intraoperative visualization in endoscopy. Pre-procedural high-resolution computed tomography (CT) or magnetic resonance imaging (MRI) data can be pre-processed into 3D models to guide navigation and support interactive surgical planning (Eberhardt et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Huang et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lachkar et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tamiya et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, traditional endoscopy relies on two-dimensional (2D) video displays that lack depth cues, often causing visual strain and surgeon fatigue during prolonged operations in confined spaces (Thavarajasingam et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe integration of AR and virtual reality (VR) capabilities into head-mounted displays (HMDs) enhances visualization beyond conventional monitors, providing immersive and spatially coherent feedback (Kassutto et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Rad et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Weidert \u0026amp; Stefan, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Whereas VR systems offer fully enclosed immersion, AR is better suited for clinical endoscopy because it allows preoperative 3D models or surgical guidance data to be overlaid directly onto intraoperative views (Li et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Linxweiler et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Okachi et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tabrizi \u0026amp; Mahvash, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This alignment reduces the need for gaze shifts between monitors and the operative field (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), a major source of cognitive and physical fatigue (Doughty et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Eberhardt et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Johnson et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). By centralizing visual and contextual information, AR-HMDs enhance workflow efficiency (L. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)(Fang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Okachi et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), improve hand\u0026ndash;eye coordination, depth perception, and reduce cognitive load through unified spatial presentation (Sadeghi et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Suter et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAR-HMDs also improve surgical navigation and spatial orientation, particularly in complex or minimally accessible procedures. The fusion of preoperative and intraoperative data within the surgeon\u0026rsquo;s field of view strengthens spatial correspondence between medical imagery and the patient\u0026rsquo;s anatomy (Hwang \u0026amp; Son, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Matsuoka et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Okachi et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pelizzo et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; L. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Such visualization facilitates precise tool positioning and real-time guidance. In a prospective randomized controlled clinical trial, Linxweiler et al. demonstrated in a prospective, randomized, controlled clinical trial that AR-enhanced navigation software was well received by surgeons across different experience levels and improved usability in endoscopic sinus surgery, without prolonging operative time or increasing complication rates (Linxweiler et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn summary, recent developments in HMDs and AR technologies are transforming how visual information is presented and perceived in endoscopic procedures. Both VST and OST systems offer complementary advantages for different clinical scenarios, while AR provides greater utility than VR by preserving direct intraoperative visualization. When combined, AR-HMDs function as an integrated display platform that can enhance spatial awareness, procedural efficiency, and overall workflow in endoscopic practice.\u003c/p\u003e\u003c/div\u003e"},{"header":"2. Methods","content":"\u003cp\u003ePreliminary examination of the literature indicated that the application of augmented reality head-mounted displays (AR-HMDs) in endoscopy remains a relatively new research area. The available studies are limited in number, heterogeneous in design, and often lack consistent quantitative measurements of system performance. As a result, a quantitative synthesis in the format of a systematic review was not feasible. Therefore, a \u003cb\u003escoping review\u003c/b\u003e approach was adopted to comprehensively summarize and map the existing research, with the aim of identifying current applications, knowledge gaps, and methodological trends in this emerging field.\u003c/p\u003e\u003cp\u003eThis review was conducted in accordance with the PRISMA-ScR guidelines, which provide a transparent methodological framework to ensure comprehensive and reproducible reporting (Tricco et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Following these guidelines, the review proceeded through five sequential phases: (1) identifying the research question, (2) identifying relevant studies, (3) study selection, (4) charting the data, and (5) collating, summarizing, and reporting the results. The optional \u0026ldquo;consultation exercise\u0026rdquo; step was not performed, as it was considered unnecessary given the exploratory scope of this review.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Research Question\u003c/h2\u003e\u003cp\u003eTo ensure a structured and comprehensive mapping of existing knowledge, this review was guided by the central question: \u003cem\u003eWhat is the role of augmented reality (AR) and head-mounted displays (HMDs) in endoscopy?\u003c/em\u003e Based on this question, the review discusses current clinical applications, benefits, limitations, and future directions of AR-enabled HMDs in various endoscopic procedures.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Literature Search\u003c/h2\u003e\u003cp\u003eA comprehensive literature search was performed in four major databases: Web of Science, Scopus, PubMed, and IEEE Xplore. Customized search strings were developed using Boolean operators and database-specific syntax to locate relevant articles, and the publication period was limited to 2014\u0026ndash;2025. The search strings used are presented in \u003cem\u003eSupplementary File 1.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eDuring the search process in each database, letters, patents, grants, abstracts, book chapters, theses etc. were excluded to retain only peer-reviewed articles for further screening. Review articles were initially included to provide contextual understanding but were excluded during the screening phase.\u003c/p\u003e\u003cp\u003eAll citations were imported into the bibliographic management software \u003cem\u003eEndNote 2025\u003c/em\u003e (Clarivate, Philadelphia, PA, USA) for efficient organization, deduplication, and subsequent reference management. Duplicated citations were identified using \u003cem\u003eEndNote\u003c/em\u003e\u0026rsquo;s \u0026ldquo;Library \u0026ndash; Find Duplicates\u0026rdquo; function and manually removed, with further duplicates manually identified and removed when found later in the process.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Study Selection\u003c/h2\u003e\u003cp\u003eTo ensure focused inclusion, only peer-reviewed articles addressing the application of AR-HMDs in endoscopic procedures were selected. Studies were excluded if they did not address all three key aspects \u0026mdash; AR, HMD, and endoscopy \u0026mdash; or were published in languages other than English. References in the included articles were also reviewed to identify additional relevant articles. In cases where the same research was reported in multiple publications, only the most recent article was retained for inclusion.\u003c/p\u003e\u003cp\u003eThe selection process is summarized in the PRISMA-ScR workflow diagram shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, which outlines the number of records identified, screened, and included at each stage.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e* The original identification included articles, clinical trials, comparative studies, meeting papers, case reports and reviews published between 2014 and 2025, while excluding letters, patents, grants, abstracts, book chapters, and theses.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e** Additional records (N\u0026thinsp;=\u0026thinsp;5) were identified through reference scanning during the screening phase and subsequently included in the full-text eligibility assessment.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, after the removal of duplicate records across databases, 181 unique articles were retained for screening. A two-stage screening process was then applied to ensure the inclusion of relevant studies. In the first stage, titles and abstracts were manually reviewed, resulting in the exclusion of 142 records that were unrelated to either endoscopy or HMDs. In the second stage, 39 full-text articles were assessed for eligibility; 8 were subsequently excluded due to irrelevance, while 5 additional records were identified through reference scanning. Ultimately, 36 studies met the inclusion criteria and were incorporated into this scoping review, comprising 28 journal articles and 8 conference proceedings for data charting and synthesis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Data Charting Framework\u003c/h2\u003e\u003cp\u003eTo ensure a structured and reproducible synthesis, the data charting framework for this scoping review was defined \u003cem\u003ea priori\u003c/em\u003e to capture both the technical and procedural dimensions of head-mounted display (HMD) applications in endoscopy, while ensuring methodological transparency and consistency during evidence synthesis. Specifically, we categorized each study according to the type of registration\u0026mdash;head-anchored (H-A), world-anchored (W-A), or object-anchored (O-A)\u0026mdash;and by image dimension (2D or 3D), following the technical taxonomy from Qian at al. (Qian et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the six resulting combinations that describe how information can be registered and displayed through HMDs in endoscopic contexts.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCategorization of HMD-displayed information in endoscopy by registration type and image dimension.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegistration\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eH-A\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2D information fixed at the same position in the HMD view.\u003c/p\u003e\u003cp\u003e\u0026bull; Intraoperative vital signs, e.g., heart rate, blood pressure, oxygen saturation.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3D information fixed at the same position in the HMD view.\u003c/p\u003e\u003cp\u003e\u0026bull; Static 3D model reconstructed from preoperative image, e.g., 3D skull.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2D overlays aligned with specific position in the environment:\u003c/p\u003e\u003cp\u003e\u0026bull; Virtual 2D view reconstructed from preoperative image, anchored in the air, e.g., virtual bronchoscopy.\u003c/p\u003e\u003cp\u003e\u0026bull; 2D video stream from intraoperative endoscopic camera, e.g., bronchoscopic view, laparoscopic view.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3D overlays aligned with specific position in the environment:\u003c/p\u003e\u003cp\u003e\u0026bull; 3D model reconstructed from preoperative image, e.g., 3D airway tree, 3D ventricle.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eO-A\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2D overlays aligned with specific landmarks:\u003c/p\u003e\u003cp\u003e\u0026bull; Preoperative image slices, anchored to the patient\u0026rsquo;s anatomy, e.g., CT, MR\u003c/p\u003e\u003cp\u003e\u0026bull; 2D video stream from intraoperative endoscopic camera, e.g., bronchoscopic view, laparoscopic view.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3D overlays aligned with specific landmarks:\u003c/p\u003e\u003cp\u003e\u0026bull; 3D model reconstructed from preoperative image, e.g., 3D airway tree, 3D ventricle.\u003c/p\u003e\u003cp\u003e\u0026bull; 3D point cloud reconstructed from intraoperative endoscopic camera, e.g., 3D point cloud from binocular endoscope.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eCategorized based on the technical classification method adapted from previous research (\u003c/em\u003eQian et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). \u003cem\u003eH-A: head-anchored, W-A: world-anchored, O-A: object-anchored.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eEach of the six configurations represents a specific balance between user-centered perception and system-centered spatial alignment. For example, head-anchored (H-A) displays prioritize continuous access to intraoperative data within the surgeon\u0026rsquo;s field of view, whereas world-anchored (W-A) and object-anchored (O-A) systems enable spatially aligned overlays that correspond to environmental or anatomical landmarks.\u003c/p\u003e\u003cp\u003eThis predefined taxonomy provides both a conceptual basis for comparing technical implementations and a methodological foundation for subsequent data synthesis. Building upon these six configurations, the following \u003cem\u003eResults\u003c/em\u003e section (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) summarizes the extracted studies in terms of HMD device type, AR registration method, endoscopic procedure category, and reported system performance parameters.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Evaluation Framework\u003c/h2\u003e\u003cp\u003eBuilding upon the categorization described above, a qualitative evaluation framework was developed to enable consistent comparison across the six HMD categories identified (H-A 2D/3D, W-A 2D/3D, O-A 2D/3D). This framework aimed to synthesize the diverse usability and performance information extracted from the included studies and to facilitate structured interpretation of the comparative results.\u003c/p\u003e\u003cp\u003eWhile some studies reported standardized subjective workload assessments such as the NASA Task Load Index (NASA-TLX), most provided only qualitative descriptions of user experience or technical performance. Because quantitative measurements (e.g., display latency, registration accuracy) were inconsistently reported, a structured yet interpretive framework was adopted to maintain methodological coherence across studies.\u003c/p\u003e\u003cp\u003eSix evaluation aspects\u0026mdash;Visibility, Ease of Setup, Ease of Use, Cognitive Efficiency, Latency, and Adaptability\u0026mdash;were defined to capture both user-centered and system-centered characteristics relevant to endoscopic AR-HMD applications. While this framework conceptually aligns with several workload dimensions of NASA-TLX\u0026mdash;such as mental demand, effort, and performance\u0026mdash;it was not intended as a direct adaptation of that scale. Rather, it extends these constructs to incorporate system-level and contextual usability factors (e.g., visibility, latency, adaptability) that are essential for evaluating AR-HMD operation within endoscopic environments.\u003c/p\u003e\u003cp\u003eEach AR-HMD configuration was initially rated independently by both authors, based on the synthesized evidence extracted from the included studies. Any discrepancies were resolved through iterative discussion until a consensus score was achieved for each evaluation aspect. The final ratings therefore represent an expert consensus\u0026ndash;based qualitative assessment, reflecting interpretive synthesis rather than quantitative measurement.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eAfter the rigorous study selection process in Section \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003e2.3\u003c/span\u003e, a total of 36 studies published between 2018 and 2025 met the inclusion criteria and were charted according to the predefined data charting framework described in Section \u003cspan refid=\"Sec9\" class=\"InternalRef\"\u003e2.4\u003c/span\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the extracted data across all included studies, outlining their respective HMD devices, AR registration methods, type of endoscopic application, study subjects, and reported system performance metrics.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of recent studies on the application of augmented reality (AR) head-mounted displays (HMDs) in endoscopic procedures.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArticle\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHMD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHMD Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAR Registration\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eContent Displayed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic Procedure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eStudy Subject\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSystem Latency (ms)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarbone et al. 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(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Cranial)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePatient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLohou et al. 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(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom (peg transfer)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e337.2\u0026thinsp;\u0026plusmn;\u0026thinsp;31.7 (1080 \u0026times; 680 pixels)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQian, M. et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eODG R-7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eH-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoluminal procedure (Laryngoscopy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026ldquo;Minimal latency\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAl Janabi et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoluminal procedure (Ureteroscopy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQian, L. et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom (peg transfer)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShen et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSony HMS-3000MT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIvan et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Cranial)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11 Patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiu et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e44 Patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWest et al. (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTransluminal procedure (Aortic intervention)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePorcine model\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArpaia et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic Surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSimulated surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.9\u0026ndash;1.1 (vitals only)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKhan et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCadaver\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMa et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMak et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eH-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOkachi et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEpson Moverio BT-35E\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eH-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoluminal procedure (Optical-navigated Bronchoscopy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSong et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Hip arthroscopy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStewart et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eH-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTorabinia et al. (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery (Myomectomy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eBovine model\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZhang et al. (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eH-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Cranial)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20 Patients (telemedicine)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMax 230 (4G connection), Max 26 (5G connection)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFang et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMAD Gaze GLOW Plus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eH-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Knee arthroscopy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFu et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKildahl-Andersen et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eH-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoluminal procedure (EM-navigated Bronchoscopy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom, Patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e330\u0026ndash;350\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeng et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Cranial)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcar et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoluminal procedure (Ureteroscopy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eForseth et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Cranial)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePatient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegrao et al. (2024)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePhantom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTohi et al. (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eO-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1 patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZhang et al. (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft HoloLens 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Thyroidectomy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1 patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN/S\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePark et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApple Vision Pro\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEndoscopic surgery (Spine)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1 patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026ldquo;No perceptible lag\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBroderick et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApple Vision Pro\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eW-A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLaparoscopic surgeries (Various)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e41 patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026ldquo;No perceived latency\u0026rdquo;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eHMD: head-mounted display, OST: optical see-through, VST: video see-through, H-A: head-anchored, W-A: world-anchored, O-A: object-anchored, N/S: not specified.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAcross the included studies, a variety of commercial head-mounted displays (HMDs) have been adapted for endoscopic visualization and intraoperative guidance. The temporal relationship between device availability and research publication is summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, highlighting a consistent lag between hardware release and academic adoption across different platforms.\u003c/p\u003e\u003cp\u003eEarly efforts were relied on industrial-grade HMDs such as the \u003cem\u003eSony HMS-3000MT\u003c/em\u003e (2013) and \u003cem\u003eODG R-7\u003c/em\u003e (2016), as well as pre-consumer developer prototype such as the \u003cem\u003eOculus Rift Development Kit 2\u003c/em\u003e (2014), which allows attaching custom module such as camera. The limited display resolution and narrow field of view of these early systems imposed clear constraints on their integration into endoscopic workflows, contributing to the notable delay between the first hardware releases and the first reported studies, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Nevertheless, these pioneering investigations demonstrated the technical feasibility of using augmented visual overlays to support surgical orientation and intraoperative decision-making.\u003c/p\u003e\u003cp\u003eResearch activity increased markedly following the release of the \u003cem\u003eMicrosoft HoloLens\u003c/em\u003e (2016) and its successor \u003cem\u003eHoloLens 2\u003c/em\u003e (2019), both of which offered improved spatial tracking, open software development kits (SDKs), and sustained developer support from Microsoft. These platforms catalyzed a transition from proof-of-concept prototypes to clinically oriented research involving real patients and cadaveric validation. More recent studies have extended to emerging VST-type HMD systems such as the \u003cem\u003eApple Vision Pro\u003c/em\u003e, reflecting a trend toward higher-resolution displays, wider fields of view, and enhanced interaction through hand or gaze tracking.\u003c/p\u003e\u003cp\u003eTo account for the highly variable number of studies per device, the median time interval between device release and study publication was calculated in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e as an indicator of research adoption speed\u0026mdash;representing the typical translational latency within each HMD ecosystem. Notably, the \u003cem\u003eApple Vision Pro\u003c/em\u003e showed two endoscopy-related studies published recently within one year of its release, underscoring the accelerating pace of clinical adoption.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHead-Mounted Displays (HMDs) and Corresponding Research Publications in Endoscopic Applications.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelease Year\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHMD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCorrelated Studies\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStudy Count\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMinimum Interval (yrs)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedian Interval (yrs)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSony HMS-3000MT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eShen et al. 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(\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn addition to the temporal and device-specific patterns summarized above, the extracted data also reveal how visualization design varies according to AR registration strategies implemented on HMD devices. As shown in \u003cb\u003eFig.\u0026nbsp;5\u003c/b\u003e, the choice among head-anchored (H-A), world-anchored (W-A), and object-anchored (O-A) registration is closely associated with whether information is presented in two or three dimensions. H-A configurations were predominantly combined with 2D overlays, reflecting their use for continuously visible intraoperative information\u0026mdash;such as vital signs or navigation cues\u0026mdash;at a fixed position within the headset\u0026rsquo;s field of view. In contrast, W-A and O-A systems more often appeared with 3D visualizations, where reconstructed anatomical or imaging data are spatially registered within the operative scene. These patterns indicate distinct pairing preferences between registration strategy and image dimension, suggesting that spatial anchoring and visual complexity are jointly configured to meet specific informational and ergonomic requirements in endoscopic procedures.\u003c/p\u003e\u003cp\u003eAs illustrated in \u003cb\u003eFig.\u0026nbsp;6\u003c/b\u003e, the same registration strategies also show distinct alignments with different endoscopic applications, reflecting how spatial anchoring is adapted to procedural demands. H-A systems are used across all application categories, underscoring the general value of readily available, fixed-position information; they are particularly common in transluminal and endoluminal procedures, where a stable visual reference aids navigation along extended luminal pathways. W-A configurations represent the most frequently adopted setup overall and dominate in general endoscopic as well as laparoscopic and thoracoscopic surgeries, where overlays fixed to the surrounding environment enhance depth perception and spatial orientation within anatomical cavities. O-A systems are the second most common approach, applied across all procedure types; by linking digital content to patient- or phantom-specific landmarks, they enable localized and high-precision guidance in complex regions.\u003c/p\u003e\u003cp\u003eCollectively, these descriptive patterns constitute a frequency-based synthesis of how AR registration methods are applied across the reviewed studies. They demonstrate the progressive adaptation of AR-HMDs from general visualization support toward context-specific augmentation, providing a conceptual foundation for the detailed analyses of individual procedural domains presented in Sections \u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Sec14\" class=\"InternalRef\"\u003e3.3\u003c/span\u003e.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1. General Endoscopic Surgery\u003c/h2\u003e\u003cp\u003eGeneral endoscopic surgery relies on precision and spatial awareness within confined anatomical cavities (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e). AR-HMDs enhance visualization by overlaying critical anatomical information, such as neural pathways or vascular structures, onto the patient\u0026rsquo;s anatomy in real-time. This improves navigation, tool positioning, and workflow efficiency, reducing risks to vital structures and enhancing surgical precision.\u003c/p\u003e\u003cp\u003eAR-HMDs have been shown to substantially enhance spatial perception and navigational precision in general endoscopic and neurosurgical procedures through 3D visualization and dynamic model integration. Even early-generation headsets, such as the \u003cem\u003eSony HMZ-T1\u003c/em\u003e, provided a convenient means of displaying preoperative 3D reconstructions within the surgeon\u0026rsquo;s view, improving situational awareness even without real-time anatomical registration (Xu et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Subsequent studies advanced this concept by superimposing 3D models onto the operative field using the \u003cem\u003eMicrosoft HoloLens\u003c/em\u003e, which improved depth perception and accuracy during complex navigation tasks (Carbone et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). More recently, the \u003cem\u003eHoloLens 2\u003c/em\u003e has enabled real-time adjustment of AR models to maintain alignment with intraoperative changes (Forseth et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). A hybrid setup incorporating both 2D and 3D overlays allowed seamless switching between visual modes in the operating room (Ivan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), representing an ideal application of AR-HMDs for flexible, spatially coherent guidance in incision planning and tumor-border identification.\u003c/p\u003e\u003cp\u003eConfined surgical spaces in joint and arthroscopic surgeries demand a high degree of precision and ergonomic efficiency, making it ideal for the integration of HMD. Appling AR overlays on \u003cem\u003eHoloLens\u003c/em\u003e in transforaminal percutaneous endoscopic discectomy not only streamlined surgical navigation but also reduced radiation exposure from conventional fluoroscopy (Liu et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similarly, while assessing the feasibility of \u003cem\u003eMAD Gaze GLOW Plus\u003c/em\u003e, a lightweight OST-type HMD, in knee arthroscopy on phantom models, AR visual guidance was confirmed to offer ergonomic improvements (Fang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003eHoloLens 2\u003c/em\u003e was applied to impose O-A AR overlay in hip arthroscopy, demonstrating an significantly increased alignment speed, improved positioning accuracy, and reduced mental effort comparing to baseline positioning without such AR assistance (Song et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which contributes to efficiency in arthroscopic procedures.\u003c/p\u003e\u003cp\u003eApplying HMDs in endoscopy also addresses the ergonomic and visual inefficiencies of traditional surgical displays. A cadaver study demonstrated the feasibility of using \u003cem\u003eHoloLens 2\u003c/em\u003e as an alternative to conventional screens for displaying 2D information, which reduced the operating room footprint while enhancing ergonomics (Khan et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although holographic feeds provided adequate coloration and resolution, tactile-visual asynchrony was identified as an area requiring refinement. Similarly, another study explored the use of a \u003cem\u003eHoloLens 2\u003c/em\u003e for displaying 3D hologram in endoscopic neurosurgery (Zhang et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), in which manual alignment of hologram to patient anatomy offered intuitive spatial cues for lesion localization and reduced the need for frequent reference to external navigation screens. These developments underscore AR\u0026rsquo;s ability to improve surgical ergonomics and efficiency, regardless of 2D or 3D content.\u003c/p\u003e\u003cp\u003eAlthough the majority of studies in the review uses OST-type HMDs, recent evidence highlights the clinical feasibility of VST-type HMDs in endoscopic surgery by integrating multimodal data in an ergonomic AR interface in high resolution. Park et al. conducted the first published intraoperative study using the \u003cem\u003eApple Vision Pro\u003c/em\u003e during an actual endoscopic procedure (Park et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In this setup, the endoscopic video feed, preoperative MRI models, and patient vital data were integrated as a W-A AR layer positioned above the surgical field, allowing the surgeon to access all visual information simultaneously without diverting attention to an external monitor. This configuration improved workflow efficiency and safety. To date, the \u003cem\u003eApple Vision Pro\u003c/em\u003e represents the first commercially available, consumer-grade VST-type HMD applied in endoscopic surgery. Although latency is often a concern with passthrough video systems, the study reported no perceptible lag when projecting a 4K endoscopic video feed onto a scalable virtual window, indicating that high-resolution VST-HMDs may offer clinically viable image quality and interaction fluidity for minimally invasive procedures.\u003c/p\u003e\u003cp\u003eAR-HMDs have also shown utility in extending surgical skills through telemedicine. \u003cem\u003eMicrosoft HoloLens\u003c/em\u003e was used in a study for remote assistance in cranial neurosurgery, demonstrating a faster 5G network significantly improved real-time interaction compared to 4G, making remote guidance feasible and efficient (Zhang et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This is the only article included in this review that focuses on using AR-HMD beyond the geographical barriers of the operating room. Furthermore, AR-guided instructions can accelerate trainee learning curves, showing the utility of AR in both surgical education and practice (Peng et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCollectively, current evidence demonstrate the versatility of AR-HMDs in general endoscopic surgery, where they enhance spatial awareness, improve real-time visualization, and alleviate ergonomic limitations within confined operative fields. Across diverse contexts\u0026mdash;from neurosurgical navigation to arthroscopic precision and telemedical collaboration\u0026mdash;HMDs have demonstrated the capacity to streamline surgical workflows and support more intuitive, context-aware decision-making. These findings position AR-HMDs as a promising adjunct technology for advancing accuracy, efficiency, and connectivity in minimally invasive surgery.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Laparoscopic and Thoracoscopic Surgery\u003c/h2\u003e\u003cp\u003eUnlike flexible endoscopic procedures, laparoscopic and thoracoscopic surgeries are performed within insufflated abdominal, thoracic, or pelvic cavities, where limited depth perception from 2D endoscopic systems and the restricted view of traditional rigid-rod scopes present major spatial challenges (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The longer duration and greater complexity of these operations also increase ergonomic strain on the operator. In this setting, HMDs offer potential advantages by providing in-situ visualization as AR guidance, making them a promising adjunct to conventional monitors.\u003c/p\u003e\u003cp\u003eIn simulated laparoscopic and thoracoscopic surgery, AR-HMDs can provide real-time augmented guidance to mitigate the spatial and ergonomic limitations of traditional laparoscopic visualization and facilitate more intuitive surgical navigation. \u003cem\u003eMicrosoft HoloLens\u003c/em\u003e has been a popular choice in several studies. For instance, it was applied in simulated laparoscopic surgeries with an O-A 2D setup, which allows surgeons to view patient vitals and surgical imagery within their direct line of sight, minimizing head movement and enabling seamless transitions between tasks (Fu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These capabilities were also extended toward O-A 3D overlays aligned with patient-specific anatomy, enabling surgeons to visualize reconstructed structures directly on the operative field and thereby improve spatial awareness and targeting accuracy (Ma et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A sequence of studies by Qian and colleagues demonstrated the feasibility and progressive refinement of AR-HMD integration into laparoscopic surgery in simulated settings. Using \u003cem\u003eHoloLens\u003c/em\u003e, the researchers successively developed O-A 3D guidance systems that registered intra-abdominal anatomy and laparoscopic instruments in real time (Qian et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; L. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Their work showed that spatially aligned 3D visualization improved depth perception, hand\u0026ndash;eye coordination, and intraoperative orientation compared with conventional 2D displays. When extended to control of a flexible endoscope, the AR-HMD interface further enhanced operative efficiency and accuracy while reducing task workload in simulated procedures (Qian et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBeyond simulation studies, AR-HMDs can bridge preoperative planning and intraoperative execution by improving spatial referencing, ergonomics, and depth perception in minimally invasive surgery. Several investigations have explored the translational potential of AR-HMDs in laparoscopic and thoracoscopic settings. Early pre-clinical work demonstrated the feasibility of using W-A 3D overlays on the \u003cem\u003eHoloLens\u003c/em\u003e to guide trocar insertion in thoracoscopy, showing that spatially registered holographic visualization could improve orientation and reduce the risk of injury to underlying structures (Lohou et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Complementary studies evaluated W-A 2D displays for simulated intraoperative use, confirming that \u003cem\u003eHoloLens 2\u003c/em\u003e could present vital signs and imaging data at fixed, ergonomically convenient locations with minimal latency (Arpaia et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Subsequently, a clinical case report illustrated the integration of mixed reality guidance in laparoscopic retroperitoneal tumor resection, where \u003cem\u003eHoloLens 2\u003c/em\u003e facilitated port-site planning and intraoperative localization of a small lesion, enhancing precision and reducing unnecessary exposure (Tohi et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEmerging evidence also supports the feasibility of VST-type HMDs for laparoscopic surgery, highlighting their potential as an alternative to traditional monitors through an immersive, high-resolution interface. Most recently, Broderick et al. reported the first published clinical use of the \u003cem\u003eApple Vision Pro\u003c/em\u003e in laparoscopic and hybrid minimally invasive procedures (Broderick et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The study demonstrated that this VST-type HMD could operate as a stand-alone surgical monitor, simultaneously displaying multiple W-A 2D video feeds in 4 K resolution with \u003cem\u003eno perceived latency\u003c/em\u003e. The system achieved low mental workload on NASA-TLX scores and provided ergonomic flexibility, allowing surgeons to position virtual displays freely within the operating room. Together with the earlier study by Park et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), this work establishes the first clinical evidence that a VST-type HMD such as the \u003cem\u003eApple Vision Pro\u003c/em\u003e can consolidate video and vital-sign data from multiple fixed monitors into an ergonomically optimized 3D workspace, improving spatial organization and workflow efficiency during endoscopic procedures.\u003c/p\u003e\u003cp\u003eBenefiting from the immersive visual presentation of AR-HMDs, they can also ease training and skill acquisition for laparoscopic surgery. When applied in laparoscopic training, AR-HMD systems provides user with flexible viewing angle based on image from the fixed laparoscopic camera (Jiang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), accelerate skill acquisition and reduce cognitive load for novice surgeons (Jayender et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Stewart et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), reduce error rates and improved task accuracy laparoscopic suturing through 3D visualization (Shen et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and offer utility in training scenarios and complex surgical tasks such as oncology and liver surgeries (Negrao \u0026amp; Maciel, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Torabinia et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). All these studies prove that AR-HMDs can provide efficient, intuitive training experience to improve accuracy of endoscopic skills.\u003c/p\u003e\u003cp\u003eCollectively, current evidence indicates that AR-HMDs enhance depth perception and spatial awareness, thereby improving tool positioning and navigation accuracy within confined cavities. Real-time augmented guidance has been shown to facilitate complex surgical maneuvers and reduce cognitive and visual workload, particularly in lengthy laparoscopic procedures. Beyond intraoperative benefits, the immersive and context-rich visualization offered by AR-HMDs also holds promise for improving training efficiency and accelerating skill acquisition in minimally invasive surgery.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Transluminal and Endoluminal Surgery\u003c/h2\u003e\u003cp\u003eTransluminal and endoluminal surgery requires navigating endoscopes through narrow anatomical pathways, such as the airway or gastrointestinal tract. In bronchoscopy where a flexible endoscope is used, maneuvering the scope in complex airway lumen space requires with limited visibility that limits the surgeon\u0026rsquo;s spatial awareness (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cem\u003e(c)\u003c/em\u003e). AR-HMDs have emerged as innovative tools to address these challenges.\u003c/p\u003e\u003cp\u003eAR-HMDs have shown considerable educational value in transluminal and endoluminal procedures by enabling immersive, hands-free visualization and real-time instructor interaction. In one airway training study using the early \u003cem\u003eODG R-7\u003c/em\u003e optical see-through headset, the live laryngoscopic camera feed was projected directly into the trainee\u0026rsquo;s visual field, allowing learners to maintain a natural line of sight with the phantom airway while simultaneously viewing an enhanced glottic image in an scalable window, although the headset\u0026rsquo;s limited field of view constrained flexibility of adjustment (M. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The addition of telestration and shared instructor perspectives further improved intubation performance and enabled real-time supervision. Overall, the study demonstrated that AR-HMDs can serve as effective educational platforms for airway management, accelerating skill acquisition and improving performance across experience levels.\u003c/p\u003e\u003cp\u003eHMDs have also been explored as AR-based navigation platforms for transluminal and endoluminal interventions, integrating multimodal imaging data to enhance spatial awareness and procedural precision. Early applications primarily focused on endovascular navigation. In a representative preclinical study, West et al. (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) employed the \u003cem\u003eMicrosoft HoloLens 2\u003c/em\u003e during an aortic intervention in a porcine model, registering a three-dimensional CT reconstruction of the aorta to fiducial markers placed on the animal\u0026rsquo;s ventral surface (West et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This study was the only one in the current review utilizing a 3D overlay rather than conventional 2D visualization. The O-A holographic alignment allowed operators to correlate the catheter\u0026rsquo;s position with vascular anatomy in real time, thereby improving spatial orientation and overall procedural awareness within the vascular lumen.\u003c/p\u003e\u003cp\u003eIn bronchoscopy, the intraluminal view provides essential spatial cues for navigating the flexible endoscope through the complex airway, and AR-HMDs offer an ergonomically convenient way to display these views as augmented overlays within the operator\u0026rsquo;s field of vision. Some studies utilized head-anchored visualization of HMD to place the AR views at a fixed position within the field of view. For example, the \u003cem\u003eEpson Moverio BT-35E\u003c/em\u003e, an OST-type HMD, was applied in bronchoscopic navigation to present live endoscopic video, virtual bronchoscopic video, and fluoroscopic images simultaneously in the operator\u0026rsquo;s field of view (Okachi et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although the HMD functions as a display-only headset without environment tracking\u0026mdash;therefore providing only a head-anchored overlay\u0026mdash;it enabled bronchoscopists to access multimodal imaging data directly within their line of sight, minimizing head movement and reliance on external monitors. In comparison, \u003cem\u003eMicrosoft HoloLens 2\u003c/em\u003e has more advanced OST capabilities, and was later evaluated for electromagnetic-guided bronchoscopy in a lung-phantom model, which successfully supported navigation to distal bronchi (Kildahl-Andersen et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These implementations of OST-type HMDs demonstrated that real-time AR can effectively assist transluminal navigation despite persistent limitations in image resolution and color fidelity\u0026mdash;even with newer devices such as the HoloLens 2.\u003c/p\u003e\u003cp\u003eBeyond bronchoscopic and vascular navigation, AR-HMDs have also been applied across diverse endoluminal procedures to improve operator performance and ergonomics. In rectoscopy, where a rigid endoscope provides direct visualization of the rectum and distal sigmoid colon, overlaying intraoperative video onto \u003cem\u003eHoloLens\u003c/em\u003e worn by surgeons, assistants, and trainees enhanced spatial awareness and ergonomic posture across the team. The system reduced perceived task load per NASA-TLX assessments, although residual latency and limited display resolution remained notable technical constraints (Huber et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). While in ureteroscopy, a study conducted the first prospective comparative study assessing the \u003cem\u003eHoloLens\u003c/em\u003e as an AR display for ureteroscopy simulation (Al Janabi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Across 72 participants of varying experience, use of the HMD significantly reduced procedural time and increased performance scores, while 95% of users rated it feasible for clinical practice and 97% endorsed its educational value. Participants also reported improved ergonomics and spatial alignment relative to conventional monitors. Building on this, integration of preoperative 3-D imaging with real-time endoscopic views through a mixed-reality \u003cem\u003eHoloLens 2\u003c/em\u003e interface enhanced stone localization accuracy, increased eye fixation time, and also reduced task load on NASA-TLX assessments, while shared gaze visualization facilitated team coordination during navigation (Acar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Collectively, these studies confirm that AR-HMDs extend beyond navigation to enhance procedural precision, ergonomic safety, and educational effectiveness across a wide spectrum of transluminal and endoluminal interventions.\u003c/p\u003e\u003cp\u003eCollectively, current evidence indicates that AR-HMDs provide tangible benefits in transluminal and endoluminal surgery by addressing the fundamental challenges of navigating narrow and tortuous luminal pathways. By integrating multimodal imaging and projecting real-time visual information directly within the operator\u0026rsquo;s field of view, these systems enhance spatial awareness, facilitate smoother endoscope manipulation, and reduce dependence on external monitors. Such context-aware visualization is particularly advantageous in airway navigation and other confined luminal procedures, where maintaining continuous orientation and ergonomic efficiency is critical.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eBuilding upon the findings presented in the previous sections, this discussion analyzes the advantages and limitations of integrating AR-HMDs across different types of endoscopic procedures and outlines future directions for refining HMD technology to better meet clinical requirements.\u003c/p\u003e\u003cp\u003eThe comparative performance of the six evaluated configurations\u0026mdash;H-A 2D, H-A 3D, W-A 2D, W-A 3D, O-A 2D, O-A 3D\u0026mdash;is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003e. These ratings were derived from the predefined evaluation framework described in Section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e2.5\u003c/span\u003e and were independently assessed by both authors based on the synthesized evidence from the included studies. Any discrepancies in the initial ratings were resolved through iterative discussion until a consensus was achieved for each evaluation aspect, ensuring the internal consistency and interpretive rigor of the final results. The six evaluation aspects\u0026mdash;\u003cem\u003eVisibility\u003c/em\u003e, \u003cem\u003eEase of Setup\u003c/em\u003e, \u003cem\u003eEase of Use\u003c/em\u003e, \u003cem\u003eCognitive Efficiency\u003c/em\u003e, \u003cem\u003eLatency\u003c/em\u003e, and \u003cem\u003eAdaptability\u003c/em\u003e\u0026mdash;were scored on a five-point Likert scale (1\u0026thinsp;=\u0026thinsp;Not usable, 2\u0026thinsp;=\u0026thinsp;Hardly acceptable, 3\u0026thinsp;=\u0026thinsp;Acceptable, 4\u0026thinsp;=\u0026thinsp;Good, 5\u0026thinsp;=\u0026thinsp;Excellent), where a score of 3 represents performance comparable to that of a conventional monitor. This approach provides a qualitative yet structured basis for comparing HMD-based configurations with traditional display systems.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRating for the Performance of HMDs in Endoscopy.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAspect\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eH-A 2D\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eH-A 3D\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW-A 2D\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eW-A 3D\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eO-A 2D\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eO-A 3D\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e(Aspect Average)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eVisibility\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e4.67\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEase of Setup\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEase of Use\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e4.33\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCognitive Efficiency\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e4.16\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLatency\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e3.83\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAdaptability\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e4.5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003e(Configuration Average)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e4.33\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e4.5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e4.16\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e4.16\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e4.33\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e4.25\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eVisibility\u003c/b\u003e: \u003cem\u003eRefers to the extent to which critical information stays consistently accessible and clearly visible during the procedure.\u003c/em\u003e \u003cb\u003eEase of Setup\u003c/b\u003e: \u003cem\u003eEvaluates the complexity and effort needed to calibrate and prepare the system for use, including hardware and software adjustments.\u003c/em\u003e \u003cb\u003eEase of Use\u003c/b\u003e: \u003cem\u003eReflects the simplicity and efficiency with which users can operate the system accurately during procedures, minimizing physical strain.\u003c/em\u003e \u003cb\u003eCognitive Efficiency\u003c/b\u003e: \u003cem\u003eMeasures how effectively the system presents information in a clear, interpretable, and intuitive manner, reducing cognitive load for grasping the information.\u003c/em\u003e \u003cb\u003eLatency\u003c/b\u003e: \u003cem\u003eAssesses the delay between input data and its display on the HMD, with lower latency indicating better real-time responsiveness.\u003c/em\u003e \u003cb\u003eAdaptability\u003c/b\u003e: \u003cem\u003eIndicates the system's flexibility and usability to accommodate various endoscopic procedures and scenarios.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese results underscore that each AR registration strategy reflects a distinct trade-off among immediacy, spatial precision, and system complexity, rather than a simple hierarchy of performance. According to these assessments, the comparative configuration averages reveal distinct performance tendencies among different AR-HMD setups. H-A systems achieved the highest configuration average (\u0026asymp;\u0026thinsp;4.42), highlighting their strengths in \u003cem\u003eease of setup\u003c/em\u003e and \u003cem\u003elow latency\u003c/em\u003e. Their straightforward alignment with the surgeon\u0026rsquo;s direct line of sight enables efficient visualization and rapid data access during time-sensitive procedures. In contrast, the spatial anchoring of O-A and W-A systems provides a more integrated anatomical perspective, supporting immersive visualization at the expense of increased calibration demands. O-A systems, averaging approximately 4.25, excel in \u003cem\u003eease of use\u003c/em\u003e and deliver the most intuitive visualization by attaching holographic data to patient- or phantom-specific landmarks, yet they are also the most complex to configure. W-A systems, with a slightly lower mean of \u0026asymp;\u0026thinsp;4.08, represent a balanced compromise between immediacy and spatial fidelity\u0026mdash;offering \u003cem\u003ecognitive efficiency\u003c/em\u003e and \u003cem\u003eadaptability\u003c/em\u003e comparable to O-A setups while requiring less extensive calibration.\u003c/p\u003e\u003cp\u003eThe aspect-level patterns depict a maturing yet still evolving technological landscape. When analyzed by evaluation aspect, the aggregated results (overall mean\u0026thinsp;=\u0026thinsp;4.25, \u0026ldquo;Good\u0026rdquo;) indicate that AR-HMDs consistently outperform conventional monitors across multiple usability domains. \u003cem\u003eVisibility\u003c/em\u003e (4.67) and \u003cem\u003eadaptability\u003c/em\u003e (4.50) received the highest ratings, underscoring the clear presentation of critical information and flexibility of application across diverse procedural contexts. \u003cem\u003eEase of use\u003c/em\u003e (4.33) and \u003cem\u003ecognitive efficiency\u003c/em\u003e (4.17) were also rated positively, reflecting improved user interaction and reduced mental workload through intuitive data visualization. In contrast, \u003cem\u003eease of setup\u003c/em\u003e (4.00) and \u003cem\u003elatency\u003c/em\u003e (3.83) emerged as relative weaknesses, illustrating that technical preparation and real-time responsiveness remain key barriers to seamless clinical adoption.\u003c/p\u003e\u003cp\u003eTaken together, these comparative results establish a structured foundation for the subsequent analysis of advantages (Section \u003cspan refid=\"Sec16\" class=\"InternalRef\"\u003e4.1\u003c/span\u003e) and limitations (Section \u003cspan refid=\"Sec21\" class=\"InternalRef\"\u003e4.2\u003c/span\u003e), elucidating how different AR-HMD configurations can be further optimized to enhance usability, spatial cognition, and workflow integration in endoscopic surgery.\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Advantages\u003c/h2\u003e\u003cp\u003eThe integration of HMDs into endoscopic procedure offers distinct advantages that mitigate long-standing ergonomic and perceptual challenges. These advantages\u0026mdash;enhanced visibility, improved ease of use, increased cognitive efficiency, and adaptability to different procedural demands\u0026mdash;collectively contribute to a more seamless and intuitive surgical workflow.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e\u003cb\u003e4.1.1. Enhanced Visibility and Spatial Awareness\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eAR-HMDs enhance surgical visibility and spatial awareness by integrating augmented information directly into the surgeon\u0026rsquo;s field of view. In conventional endoscopic procedures, surgeons must frequently shift their line of sight between the operative field and external monitors to acquire critical data, disrupting workflow and reducing situational awareness (Johnson et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). H-A configurations resolve this issue by keeping essential information consistently aligned with the surgeon\u0026rsquo;s gaze, ensuring uninterrupted access to visual cues. W-A systems stabilize data spatially within the operating environment, providing a broader contextual view that improves orientation during complex maneuvers. O-A systems further refine visibility by projecting holographic 3D overlays directly onto anatomical structures in real time (L. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) (Ivan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), allowing intuitive, anatomy-referenced visualization that supports precise tool navigation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e4.1.2. Improved Ease of Use\u003c/h2\u003e\u003cp\u003eBy consolidating multiple visual and control interfaces into a single immersive platform, HMDs streamline endoscopic workflows and reduce operator fatigue. In traditional setups, surgeons must rely on several external monitors and input devices, resulting in cumulative neck and eye strain during lengthy or complex procedures (Johnson et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Once the visual overlay is configured prior to surgery, HMDs enable hands-free or minimally interactive control\u0026mdash;such as eye-tracking and gesture-based commands\u0026mdash;allowing smoother task execution with reduced physical effort. H-A systems keep critical data within the surgeon\u0026rsquo;s natural line of sight, eliminating repetitive head movements. W-A and O-A configurations position 2D or 3D visualizations spatially close to the operative field or directly onto anatomical structures, thereby reducing the disruption caused by consulting external displays (Lin et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In addition, integrating AR visualization into the surgical workflow helps maintain focus on the operative field and alleviates physical fatigue, particularly during prolonged procedures (Fang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e4.1.3. Improved Cognitive Efficiency\u003c/h2\u003e\u003cp\u003eIntegrating augmented reality into HMDs enhances cognitive efficiency by reducing the mental effort required to process dispersed information during endoscopic procedures. In traditional workflows, surgeons must mentally consolidate data from multiple sources\u0026mdash;such as preoperative imaging, intraoperative sensors, and real-time endoscopic visuals\u0026mdash;which increases cognitive load and slows decision-making. AR-HMDs address this challenge through centralized visualization platforms that overlay key information, including anatomical landmarks, tool trajectories, and sensor feedback, directly within the surgeon\u0026rsquo;s field of view (Al Janabi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kildahl-Andersen et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). By presenting these data streams simultaneously in a unified and interpretable format, the systems enable seamless integration of multimodal information and reduce the interruptions inherent to conventional monitor-based setups.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003e4.1.4. Workflow Adaptability and Training Benefits\u003c/h2\u003e\u003cp\u003eAR-HMDs enhance surgical adaptability and training efficiency by extending visualization and collaboration beyond conventional operating settings. Their immersive and spatially flexible displays allow remote guidance and real-time teleassistance: the Microsoft HoloLens enabled effective remote support in cranial neurosurgery, with 5G connectivity providing smooth interaction compared to 4G networks (Zhang et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In training contexts, AR-HMDs facilitate intuitive, hands-free learning through immersive 3D visualization. Studies in laparoscopic simulation demonstrated improved task accuracy, faster skill acquisition, and reduced cognitive load for novice surgeons (Jayender et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jiang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shen et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Stewart et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similarly, AR-guided laryngoscopic training using the ODG R-7 improved intubation performance through shared instructor views and telestration (M. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBy integrating augmented visualization, intuitive control, and adaptive display design, AR-HMDs create a unified platform that enhances visibility, usability, and cognitive performance during endoscopic procedures. These systems enable surgeons to access and interact with critical information directly within their field of view, maintaining workflow continuity while reducing physical and mental strain. Collectively, these advantages establish AR-HMDs as effective tools for improving precision, efficiency, and situational awareness in minimally invasive surgery.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Limitations\u003c/h2\u003e\u003cp\u003eDespite the advantages discussed above, large-scale adoption of AR-HMDs in endoscopy remains constrained by several critical limitations. The most pressing challenges include excessive latency in real-time data processing, ergonomic discomfort during prolonged use, and the technical complexity of workflow setup\u0026mdash;particularly in achieving stable and accurate 3D image registration. These limitations not only restrict current clinical deployment but also highlight the need for coordinated improvements in hardware design, system optimization, and human\u0026ndash;machine integration to ensure sustainable clinical usability.\u003c/p\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e4.2.1. System Performance Constraints\u003c/h2\u003e\u003cp\u003eThe most critical technical limitation of current AR-HMDs in endoscopy lies in system latency and its impact on visual accuracy and user comfort. Latency\u0026mdash;the delay between image capture and display\u0026mdash;remains substantially higher than the perceptual threshold required for real-time feedback, often exceeding 300 ms in 3D-capable HMD systems (Kildahl-Andersen et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; L. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Such delays can cause misalignment between virtual and physical objects, leading to visual fatigue or motion sickness (Andrievskaia et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kundu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Park et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This issue is particularly detrimental in high-precision procedures such as neurosurgery, where even millisecond-level discrepancies may compromise spatial accuracy and increase surgical risk. Studies have shown that maintaining latency below approximately 20 ms can effectively prevent these effects (Kundu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), a benchmark far from what current systems achieve. Multiple review studies have reached similar conclusions, emphasizing latency reduction as a prerequisite for achieving stable and comfortable AR experiences (Anua et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Stauffert et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEfforts to address latency depend on improvements in both hardware\u0026mdash;including faster GPUs, optimized rendering pipelines, and low-latency transmission\u0026mdash;and software, such as adaptive algorithms for real-time tracking and image registration. While Moore\u0026rsquo;s law no longer progresses exponentially (Moore, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), innovations in 3D transistor design, advanced lithography, and high-bandwidth communication (e.g., 5G and 6G uRLLC) may enable future reductions in latency (Burg \u0026amp; Ausubel, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kumari et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Continued advances in these domains are essential to achieving the sub-20 ms performance required for fatigue-free, clinically reliable AR-HMD operation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003e4.2.2. Ergonomic Limitations\u003c/h2\u003e\u003cp\u003eDespite improving intraoperative visibility, current AR-HMDs impose notable ergonomic limitations that hinder their sustained clinical use. Although HMDs can reduce the need for head movement, they often introduce new comfort issues\u0026mdash;particularly during prolonged procedures (Fu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). VST-type HMDs such as the \u003cem\u003eOculus Rift\u003c/em\u003e and \u003cem\u003eApple Vision Pro\u003c/em\u003e are bulkier and heavier because of integrated processors and cameras for higher performance (Broderick et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Jayender et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Park et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Studies have shown that while short-term fatigue is minimal, poor weight distribution can cause neck discomfort and visual strain over longer use (Ito et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The widely adopted \u003cem\u003eMicrosoft HoloLens\u003c/em\u003e, released in 2016 and used in half of the reviewed studies, also suffers from a limited field of view (34\u0026deg;), constraining the visibility and the amount of information that can be presented within the overlay (Al Janabi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDifferent fixation mechanisms\u0026mdash;ear hooks, headbands, and overhead straps\u0026mdash;have been explored to mitigate these effects. Headbands are often difficult to adjust effectively (Al Janabi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e),, whereas overhead straps distribute weight more evenly across the head, improving comfort during extended use, especially with heavier HMDs (Qian et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). To make AR-HMDs more practical for endoscopic applications, especially in lengthy laparoscopic procedures, future designs must prioritize lighter materials, better weight balance, and adjustable ergonomics to accommodate diverse clinical users and settings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\u003ch2\u003e4.2.3. Workflow and Setup Challenges\u003c/h2\u003e\u003cp\u003eAnother key limitation of AR-HMDs lies in the complexity of workflow setup, particularly in achieving accurate image registration for 3D visualization. For world-anchored and object-anchored systems reviewed in this study, registration between virtual models and the patient\u0026rsquo;s anatomy remains the most technically demanding step before clinical use. Integrating multimodal imaging\u0026mdash;such as CT, MRI, and real-time endoscopic data\u0026mdash;requires precise spatial alignment, which is often manual and highly operator dependent. Among the reviewed systems, only one employed combined fiducial and simultaneous localization and mapping (SLAM) tracking to partially automate this process (L. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); all others relied on manual initial registration and subsequent re-registration to compensate for tracking drift during procedures (Ivan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Qian et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; L. Qian et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Suter et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This dependency on manual calibration not only prolongs setup time but also increases the risk of misalignment as the surgical field changes. Overall, the need for repeated manual registration continues to constrain workflow efficiency, underscoring that improved tracking stability and user-friendly calibration protocols are essential for broader clinical translation of AR-HMD systems.\u003c/p\u003e\u003cp\u003eOverall, the limitations outlined in this section highlight the key technical and practical barriers that must be overcome for AR-HMDs to achieve reliable clinical integration. Addressing these challenges requires a comprehensive approach that advances both technology and usability. Reducing latency through faster rendering pipelines and high-bandwidth transmission will be essential for achieving stable, fatigue-free visualization. Ergonomic refinements\u0026mdash;including lighter materials and better weight distribution\u0026mdash;will enhance comfort and make prolonged use more practical. Finally, progress in automatic registration methods such as SLAM and real-time image processing is expected to replace manual calibration and fiducial-based alignment (Marchesi et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Reimer et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sun et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), streamlining setup and improving workflow efficiency. Collectively, these developments will determine whether AR-HMDs can transition from experimental feasibility to reliable clinical adoption.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis scoping review synthesized 36 studies published over the past decade on the application of augmented reality head-mounted displays (AR-HMDs) in different categories of endoscopic procedures. To organize and compare findings across heterogeneous systems, a structured qualitative framework based on a customized Likert-scale assessment was applied. This approach provided a consistent basis for summarizing user- and system-centered characteristics where quantitative indicators were unavailable, enabling a more coherent interpretation of existing evidence.\u003c/p\u003e\u003cp\u003eSeveral methodological constraints should be acknowledged. Research in this domain remains in an early stage, with limited sample sizes and inconsistent reporting of key performance parameters such as latency. The qualitative rating method, although structured, introduces subjectivity, as only two reviewers participated and inter-rater reliability was not formally tested. In addition, variability in system design within each configuration type may have contributed to inconsistent findings, limiting the ability to establish definitive best practices for specific clinical contexts.\u003c/p\u003e\u003cp\u003eOverall, the synthesized evidence indicates that AR-HMDs can enhance surgical visibility, usability, and cognitive efficiency while also supporting emerging applications in telemedicine and immersive training. Nevertheless, widespread clinical adoption remains constrained by challenges related to latency, ergonomics, and workflow complexity. Continued progress will depend on collaborative efforts among engineers, clinicians, and regulators to improve technical performance, usability, and standardization. As these technologies mature, AR-HMDs are expected to become more seamlessly integrated into modern endoscopic practice.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMingwei Cui: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing \u0026ndash; original draft, Writing \u0026ndash; review and editing. Xiaorong Gao: Conceptualization, Funding Acquisition, Project administration, Resources, Supervision, Writing \u0026ndash; review and editing.\u003c/p\u003e\n\u003cp\u003eBoth authors agreed with the content and that they all gave explicit consent to submit and that they obtained consent from the responsible authorities at the institute/organization where the work has been carried out, before the work is submitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOpen access funding provided by the National Natural Science Foundation of China (U2241208, 62171473, 61671424), the National Key Research and Development Program of China (2022YFC3602803, 2023YFF1205300), Key Research and Development Program of Ningxia (2023BEG02063).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis paper is a scoping review of published studies, and since it does not involve primary data collection, there is no data to make available for public access. Similarly, as this paper is a review paper without involving human participants, no ethics approval or informed consent was necessary.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOpen Access\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third-party material in this article are included in the article\u0026rsquo;s Creative Commons license, unless indicated otherwise in a credit line to the material. 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Mobile internet-based mixed-reality interactive telecollaboration system for neurosurgical procedures: technical feasibility and clinical implementation. \u003cem\u003eNeurosurg Focus\u003c/em\u003e,\u003cem\u003e 52\u003c/em\u003e(6), E3. https://doi.org/10.3171/2022.3.Focus2249 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Head-mounted displays, augmented reality, endoscopy, surgical navigation, 3D visualization","lastPublishedDoi":"10.21203/rs.3.rs-8098102/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8098102/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAugmented reality\u0026ndash;enabled head-mounted displays (AR-HMDs) are emerging as alternative visualization interfaces in endoscopic surgery. This scoping review maps current applications, methodological characteristics, and performance trends of AR-HMDs across different procedural contexts.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eFollowing the PRISMA-ScR framework, peer-reviewed articles published between 2014 and 2025 were searched in Web of Science, Scopus, PubMed, and IEEE Xplore. Thirty-six studies met inclusion criteria and were charted using a predefined data framework that categorized HMD configurations by registration type and imaging dimension. A qualitative Likert-scale evaluation further compared six representative configurations across visibility, usability, and latency dimensions.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAR-HMDs have been applied in endoscopic, laparoscopic and thoracic, transluminal and endoluminal procedures, enhancing spatial awareness, navigation precision, and training efficiency. Head-anchored systems provide optimal responsiveness and easy o setup, whereas world- and object-anchored setups enable more immersive 3D integration with anatomical structures.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e\u003cp\u003eEvidence indicates that AR-HMDs can enhance visibility, usability, and cognitive efficiency compared with traditional displays, though challenges remain in latency, ergonomics, and setup complexity. Further technical optimization is needed before these systems can achieve wider clinical adoption.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eAR-HMDs have demonstrated promising applicability across various endoscopic procedures and may play an increasingly important role in enhancing visualization and workflow efficiency as technical and ergonomic limitations are further addressed.\u003c/p\u003e","manuscriptTitle":"Current Perspectives on Augmented Reality and Head-Mounted Displays in Endoscopy: A Scoping Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 09:04:36","doi":"10.21203/rs.3.rs-8098102/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ace7a80d-4844-4714-8d22-a87e0370cae6","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-08T17:23:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-26 09:04:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8098102","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8098102","identity":"rs-8098102","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}