Comprehensive bibliometric and visualized analysis of research on front crawl biomechanics published from 1984 to 2023

Comprehensive bibliometric and visualized analysis of research on front crawl biomechanics published from 1984 to 2023 | 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 Comprehensive bibliometric and visualized analysis of research on front crawl biomechanics published from 1984 to 2023 Dongxiang HUANG, Keyi ZHANG, Huang Kay CHOW This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4023457/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 The biomechanical review of front crawl (FC) swimming can enhance athletes' technical proficiency and prevent sports injuries. Over the last 39 years, considerable research has been conducted on FC biomechanics. However, there exists a need for more bibliometrics studies. The objective of this study is to create a knowledge map highlighting the prominent research areas and cutting-edge frontiers in the field of FC biomechanics. Methods Using Citespace, this study conducts bibliometric and visualization analysis of 508 articles in the field of FC biomechanics sourced from the Web of Science Core Collection database. The study focuses on collaboration networks among authors. Additionally, it examines the co-citation analysis of journals and performs co-occurrence, cluster, and burst term analysis on keywords. Results Ricardo J. Fernandes is the most influential author. We found that the journal INT J SPORTS MED has been the most frequently cited publication. The popular keywords in this field include velocity, performance, and swimmers. Moreover, we identified several burst keywords, such as body roll, stroking characteristics, and motor control. Through cluster analysis, we identified that body roll, drag, motor control, and training are highly interconnected concepts in this domain. Conclusion The forefront of research in the field of FC biomechanics has evolved from a focus on fundamental techniques to addressing complex problems and, subsequently, validating research methods and data reliability. Future research directions may consider separately analyzing the impact of shoulder and hip rotation on freestyle performance, investigating the effects of training on freestyle starts or turns, and exploring the potential and application scope of inertial sensors. By integrating other technologies and methods, this research aims to provide comprehensive support and guidance for the training and performance of swimmers. Front Crawl Swimming Sports Biomechanics Citespace Knowledge Domain Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Background Competitive swimming comprises four swimming styles: front crawl (FC) swimming, backstroke, breaststroke, and butterfly. Among these, FC is recognized for its minimal resistance, high speed, and reduced effort compared to other strokes[ 1 , 2 ]. In the Olympic Games, there are 32 swimming events, with 13 dedicated to FC. Additionally, FC is incorporated into medley and medley relay events. Consequently, FC is a significant indicator o f a country's competitive swimming strength [ 3 ]. Numerous countries and research institutions focus on enhancing FC techniques, and the field of sports biomechanics has provided a scientific foundati on for such improvements[ 4 ]. Sports biomechanics examines athletes' mechanical characteristics and control mechanisms during exercise[ 5 ]. It facilitates a deeper understanding of swimmers' movement techniques, power output, and dynamic characteristics, optimizing training methods, improving sports performance, and preventing sports injuries[ 6 ]. Consequently, many scholars have taken a keen interest in studying FC biomechanics. While significant research findings have emerged in this field over the last 39 years, there remains a need for systematic analysis and evaluation of the existing literature. Bibliometric review, a systematic analysis and measurement approach for scientific research literature[ 7 ], offers insights into the development trends, impact, quality, relationships, and emerging themes among different publications [ 8 ], by collecting, organizing, and analyzing relevant literature data, a bibliometric review helps overcome the subjective biases of narrative literature reviews[ 9 ]. Citespace, a bibliometric tool, constructs network maps of scientific literature to uncover citation relationships, thematic evolution, and research frontiers[ 9 ]. Therefore, this study employs Citespace software to provide a comprehensive overview of the research history in FC biomechanics based on a thorough analysis of research achievements over the last 39 years. This study aims to identify the structure, dynamic evolution patterns, and trends within this field and offer valuable insights for future scholars investigating FC biomechanics. 2. Methodology 2.1 Data Collection The database for this study consists of data acquired from the SCI-Expanded, SSCI, CPCI-S, and CPCI-SSH databases within the Web of Science™ Core Collection. To collect the relevant literature, Boolean operators (AND, OR) were applied to combine keywords. The initial searches were conducted using the following terms: #1: TS = (Biomechanic* OR Kinematic* OR Kinetic* OR ‘Force plate’ OR ‘force platform’ OR ‘Motion capture’ OR EMG OR Electromyography OR ‘Muscle activation’ OR Hydrodynamic* OR mechanic*), #2: TS = (‘Front crawl’ OR FC OR Freestyle), and #3: TS = (Swim OR Swimming). These searches yielded 3,666,042, 3,252, and 75,674 retrieved records, respectively. Subsequently, a combined search was performed using #1 AND #2 AND #3. The search results were refined to include only ‘Article’ and ‘Review Article’ document types and were restricted to the English language. Articles that did not align with the subject of FC biomechanics were excluded. Ultimately, 508 relevant articles were obtained and utilized as the research data for this study. The search was conducted up to December 31, 2023, ensuring the inclusion of the most recent literature available. 2.2 Research tool In this study, the Java-based software program called Citespace (version 6.2.R3) was utilized to visually analyze the field of FC biomechanics. Citespace allows for the extraction and reorganization of author, institution, country, and keyword information from literature, facilitating the visualization of analytical results. By employing Citespace, precise tracking, and analysis of frontier trends and the dynamic evolution of research fields in FC biomechanics were made possible[ 9 ]. 2.3 Parameter setting The parameters were set as follows: Time slicing: each year as a time slice from 1984 to 2023; Term source: title, abstract, author keywords, and keywords plus; Node types: author, Journal, keywords; Selection criteria: "g-index = 25" for author, Journal, "g-index = 10" for Keywords; and Pruning options: Pathfinder, pruning the merged network. 3. Results 3.1 General information Annual Publication Analysis The trend in annual publications of core papers in the study of FC biomechanics over the past 39 years is depicted (Fig. 1). It can be observed that the first paper in this field was published in 1984, and there has been a steady increase in the number of annual publications in the field, with slight fluctuations. Figure 1 The annual number of publications from 1984 to 2023. Author Analysis As depicted in Table 1 , the authors in the field of FC biomechanics, aside from, Ricardo J. Fernandes, are Tiago M. Barbosa, Daniel A. Marinho, João Paulo Vilas-boas, and Jorge E. Morais, all of whom have a publication volume exceeding 30 articles. Furthermore, they all exhibit high centrality rankings, with Ricardo J. Fernandes maintaining the first position, Joao Paulo Vilas-boas ranking second, and Tiago M. Barbosa ranking third. Table 1 Top 10 authors with the highest publications and centrality Rank High publications author High centrality author Name Count Name Centrality 1 Fernandes, Ricardo J 61 Fernandes, Ricardo J 0.15 2 Barbosa, Tiago M 53 Vilas-boas, Joao Paulo 0.08 3 Marinho, Daniel A 46 Barbosa, Tiago M 0.07 4 Vilas-boas, Joao Paulo 45 Seifert, Ludovic 0.06 5 Morais, Jorge E 30 Chollet, Didier 0.03 6 Figueiredo, Pedro 29 Hellard, P 0.03 7 Seifert, Ludovic 28 Marinho, Daniel A 0.02 8 Chollet, Didier 25 Sanders, Ross H 0.02 9 Sanders, Ross H 18 Gonjo, Tomohiro 0.02 10 Costa, Mario J 18 Takagi, Hideki 0.02 Journal Analysis The information on the top 10 cited journals is presented in Table 2 . The most significant number of citations, as well as the highest centrality, were observed in the International Journal of Sports Medicine. Table 2 Top 10 cited journals and the importance index (centrality value) Rank Journal Count Centrality Publishing Country/Region IF 1 International Journal of Sports Medicine 373 0.12 Germany 2.5 2 Journal of Sports Sciences 363 0.04 United Kingdom 3.4 3 Medicine and Science in Sports and Exercise 360 0.01 United States 4.1 4 Journal of Biomechanics 300 0.02 Netherlands 2.4 5 European Journal of Applied Physiology 283 0.01 Germany 3 6 Journal of Applied Biomechanics 269 0 United States 1.4 7 Sports Medicine 268 0 New Zealand 9.8 8 Journal of Strength and Conditioning Research 231 0 United States 3.2 9 Human Movement Science 222 0.02 Netherlands 2.1 10 Journal of Science and Medicine in Sport 190 0 Australia 4 3.2 Keyword co-occurrence analysis The 508 articles were imported into Citespace, with the "time slice length" set to 1. The selection criteria used were K = 10, LRF = 3.0, L/N = 10, LBY = 5, and e = 1.0, and the Pathfinder strategy was applied, resulting in the acquisition of a keyword co-occurrence map for FC biomechanics research, which comprised 264 nodes and 523 links (Fig. 2). The top 10 keywords in terms of frequency and centrality are presented in Table 4. It is observed from Fig. 6 and Table 3 that front crawl exhibits the highest frequency of occurrence. Notably, although keywords such as biomechanics, active drag, and efficiency do not appear in the top 10 in terms of frequency, their centrality is relatively high. Figure 2 Co-occurrence analysis of Keywords Table 3 Top 10 Keywords with the highest publications and centrality Rank High-frequency keywords High centrality keywords Keywords Count Keywords Centrality 1 front crawl 159 biomechanics 0.44 2 velocity 145 exercise 0.31 3 performance 125 active drag 0.28 4 swimmers 89 swimmers 0.21 5 distance 72 efficiency 0.19 6 parameters 66 front crawl 0.18 7 exercise 59 energetics 0.18 8 arm coordination 57 competitive swimming 0.16 9 drag 55 coordination 0.15 10 energy cost 48 drag 0.14 An analysis of burst terms in the field of FC biomechanics was conducted based on keyword co-occurrence. The burst terms map (Fig. 3) was obtained and arranged in ascending order of time. It was observed that the time periods of keyword emergence were not independent; there was a cross-overlap in time, and the content was carried forward and backwards. Figure 3 Top 8 keywords in burst impact 3.3 Cluster analysis Using the log-likelihood algorithm (LLR), a cluster analysis was conducted on the keywords in the field of FC biomechanics based on the method of keyword co-occurrence. This analysis produced a cluster map comprising 264 nodes and 523 links (Fig. 4). The figure exhibits a Q value of 0.722 and an S value of 0.8657, of visually representing the top 11 clusters. Figure 4 Cluster map of keywords 4 Discussion 4.1 General information The number of publications and the changing trends in annual publication quantities indicate the overall significance and evolving interests of scholars in a particular field[ 7 ]. The annual publication rate in the field of FC biomechanics has exhibited a steady increase with minor fluctuations. Before 2008, the number of publications in this field could have been higher, with fewer than ten articles. This initial stage can be considered as the early phase of research. Scholars' attention towards FC biomechanics has continued to grow since 2008, resulting in a peak in the number of publications in 2023. During this period, researchers have shown a high level of enthusiasm for studying FC biomechanics, actively publishing articles, and promoting the development of the field. This can be regarded as the peak period of research. Based on the publication trend line, it can be inferred that the annual publication rate is expected to continue increasing in the future, reflecting the ongoing development and advancement of research in this field. Centrality, as defined by Chen (2006), measures an author's significance and impact within a network[ 9 ]. Authors with high centrality indicate their importance and influence within the collaborative network. In this regard, Ricardo J. Fernandes Joao Paulo Vilas-boas Tiago M. Barbosa Ludovic Seifert Didier Chollet Daniel A. Marinho Ross H. Sanders not only demonstrate a substantial number of publications but also exhibit a considerable value of centrality. This suggests that they hold notable influence and standing within the academic field. It is noteworthy that Hellard, P, Gonjo, Tomohiro, and Hideki, Takagi while not ranking within the top 10 list in terms of publication count, possess relatively high centrality. This implies that they also hold significant influence and importance within the field of FC biomechanics. These findings provide valuable insights for future scholars, offering information on key authors in the field of FC biomechanics. The citation count of INT J SPORTS MED, J SPORT SCI, MED SCI SPORT EXER, and J BIOMECH, all exceeding 300, indicates that their published research findings have a high impact and recognition in FC biomechanics. These journals are widely acknowledged by other researchers and are considered to have high research quality and academic value. In the analysis of journal citations, high centrality represents the importance of the journal[ 10 ]. INT J SPORTS MED, in addition to having a large number of citations, also has high centrality, indicating its significant position and extensive collaborative relationships in FC biomechanics. This suggests that the journal is crucial in disseminating research and fostering collaborations within the field. Future researchers can delve into FC biomechanics by collecting papers from these top journals to explore the latest research findings, methodologies, and advancements. 4.2 Hotspots and Frontiers From an epistemological standpoint, keywords with high frequency and centrality often signify topics researchers collectively emphasize during a specific period, signifying research novelty and frontiers[ 11 ]. Citespace assesses the proximity among a set of keywords by tallying their co-occurrence frequency in the literature, thereby facilitating the identification of research hotspots within specific disciplines[ 9 ]. In FC biomechanics, the term ‘front crawl’ exhibits the highest frequency, appearing 159 times, as it’s the term we used in the literature search. Keywords such as ‘velocity’ and ‘performance’ surpass 100 occurrences, alongside ‘swimmers,’ ‘distance,’ ‘parameters,’ and ‘exercise,’ which have guided the research trajectory in FC biomechanics over the past 39 years. Keywords with centrality exceeding 0.01 indicate extensive research activity and heightened impact[ 12 ]. Notably, keywords such as ‘biomechanics,’ ‘exercise,’ ‘active drag,’ and ‘swimmers’ possess centrality values surpassing 0.1, underscoring their substantial influence and role as focal points in FC biomechanics research. High-frequency keywords reveal researchers’ profound interest in fundamental characteristics and FC performance. Keywords of high centrality highlight researchers’ focus on optimizing FC performance and enhancing swimming efficiency, particularly through the exploration of biomechanical characteristics, training methodologies, and energy expenditure in FC. Under the definition provided in previous research, frontier research pertains to a collection of emerging and dynamic concepts along with potential research questions [ 12 ]. It accentuates novel trends and emerging features, representing a central topic that a body of literature, characterized by burst terms, focuses on during a specific time period. Burst terms are keywords that experience a substantial increase in frequency within a delimited timeframe, signifying emerging research directions and significant advancements in the field[ 13 ]. According to Fig. 7, the burst keywords in the field of FC biomechanics have undergone the evolutionary process of the budding stage (1999–2015), the active exploration stage (2016–2021), and the deepening advancement stage (2022–2024). In the budding stage, the burst keywords include "Body roll," "stoking characteristics," "motor control," and "arm coordination." In the active exploration stage, the emerging keywords are "acceleration," "power," and "kinetics." The emerging keywords in the deepening advancement stage include "sprint" and "reliability." During the budding stage, burst terms encompassed ‘Body roll,’ ‘stroking characteristics,’ ‘motor control,’ and ‘arm coordination.’ In the active exploration stage, burst terms included ‘acceleration,’ ‘power,’ and ‘kinetics.’ Lastly, burst terms comprised ‘sprint’ and ‘reliability’ in the deepening advancement stage. Initially, researchers primarily concentrated on swimmers' fundamental movement characteristics and technical elements. Establishing a comprehensive understanding of these foundational aspects is a basis for subsequent research in FC biomechanics. As researchers introduced advanced equipment and delved deeper into the field, their focus expanded to areas such as motor control, power output, and dynamics. Subsequently, scholars directed their attention towards sprint swimming, validating research data, and ensuring the reliability of research equipment and data. This progression reflects researchers' unwavering pursuit of meticulousness and comprehensiveness. The field of FC biomechanics embodies a progressive accumulation of knowledge. Through continuous research achievements, scholars have propelled the development of FC biomechanics from focusing on basic techniques to exploring complex issues and validating data reliability. 4.3 Research trend Different clusters of keywords can be formed by analyzing the high-frequency keywords used in the article, each representing a specific theme. This method can assist researchers in quickly understanding the research dynamics and trends in the field[ 9 ]. The Q value of 0.722 in Fig. 8 indicates a significant clustering structure, as it is greater than 0.3[ 9 ]. Additionally, the S value of 0.8657, which is greater than 0.5, suggests the high credibility of the clustering. By analyzing the cluster (Fig. 8) and interpreting the references associated with these clusters, we have identified four main research trends in the field of FC biomechanics: Relationship between body rotation and FC performance In FC, swimmers generate forward propulsion by employing alternating arm strokes. This process involves rotational movement of the trunk along the body's longitudinal axis, commonly referred to as body rotation. Body rotation control is regulated by the motor control system, which modulates muscle contraction and relaxation. The magnitude and direction of the principal moment of inertia influence the stability and control of body rotation. Consequently, this topic encompasses clusters #2, #9, #0, and #10 (Fig. 4). The relationship between body rotation and FC performance has garnered considerable scholarly attention. For instance, Hay et al. (1993) were pioneers in utilizing computer simulation models to simulate FC movements[ 14 ]. Their research revealed that body rotation can lead to deviation of the hands towards the body's midline during the pull phase, thereby impacting stroke technique. Building upon Hay's work, Payton et al. (1997) further explored the influence of body rotation on arm stroke velocity and trajectory[ 15 ]. The findings demonstrated that increased body rotation significantly affected hand trajectory and enhanced stroke velocity, thereby enhancing propulsion. Furthermore, studies have examined differences in body rotation between breathing and non-breathing conditions using videography. For example, Payton et al. (1999) discovered that swimmers exhibited larger body rotation angles during breathing (66 ± 5°) compared to non-breathing conditions (57 ± 4°)[ 15 ]. De Souza Castro et al. (2007) reported that most swimmers demonstrated increased body rotation during breathing, whereas triathletes displayed no significant variation in body rotation between breathing and non-breathing conditions[ 16 ]. These studies often treat body rotation as a unified concept, disregarding the distinct contributions of shoulder and hip rotation. Research has revealed variations in the magnitude and timing of shoulder rotation and hip rotation among different swimmers and even between the left and right sides of the same swimmer[ 17 – 20 ]. Consequently, to gain a more comprehensive understanding of the movement characteristics of body rotation, it is imperative to analyze the rotation of the shoulders and hips separately. This approach would yield more detailed outcomes and enable readers to comprehend better the underlying mechanisms governing body rotation underlying mechanisms. The impact of training on biomechanical parameters in FC This topic encompasses clusters #3, #4, and #10 (Fig. 4). Training methods commonly employed in swimming include strength training, resistance training, core training, and others. These training modalities have been shown to enhance athletes' muscle strength, swimming efficiency, body stability, and muscle explosiveness, consequently leading to improved FC performance[ 21 ]. In swimming, time is a critical performance indicator, with velocity being a primary determinant of time. Stroke rate and length are crucial factors influencing swimming velocity and positively contribute to overall swimming performance[ 22 ]. Increasing stroke rate and length can enhance velocity[ 17 , 23 ] as velocity is the product of stroke rate and length[ 24 ]. Therefore, numerous studies evaluate the impact of training on FC performance by measuring stroke rate and length. For instance, research has demonstrated that resistance training or core training can improve stroke length[ 25 , 26 ]. Girold et al. (2012) found that strength training has a maximal positive effect on enhancing stroke length[ 27 ]. This can be attributed to the fact that increasing stroke length necessitates swimmers to possess higher muscle strength to exert greater force and overcome water resistance[ 28 , 29 ]. Thus, after several weeks of strength training, swimmers' muscle strength improves, resulting in positive advancements in stroke length. However, the findings of studies by Gourgoulis et al. (2019) and Karpiński et al. (2020) indicated that strength or resistance training led to improved stroke rate but decreased stroke length[ 30 , 31 ]. While an increase in stroke rate typically corresponds to a decrease in stroke length, training can still enhance FC performance through strength and resistance training[ 32 ]. Crowley et al. (2017) highlighted in their research report that most training exerts a greater influence on stroke rate than stroke length, particularly after several weeks of strength and endurance training, where the impact on stroke rate becomes more significant[ 33 ]. The stroke rate is crucial for maximizing velocity[ 17 ]. However, further research is needed to determine the optimal balance between stroke rate and length for improved FC performance. Elastic training has been shown to positively impact maximal lower limb strength and explosiveness[ 34 , 35 ], making it highly valued in swimming training. Studies have demonstrated that elastic training is crucial for optimizing FC start performance[ 36 – 38 ]. Elastic training enhances joint torque in the lower limbs and enables control of the resultant force vector direction, thereby improving FC start performance[ 37 ]. Rejman et al. (2017) established that elastic training enhances average speed during the take-off, flight, and glide phases, resulting in reduced start time and optimized FC start performance[ 38 ]. Additionally, investigations have examined the impact of core muscle training on FC turn performance. Karpiński et al. (2020) demonstrated that six weeks of core muscle training significantly reduced the time for the 5-meter section after the turn and improved the average speed for the same section[ 31 ]. Start and turn play a crucial role in FC performance. However, there is currently a dearth of research concerning the effects of training on the biomechanics of FC start or turn. Thus, future research could focus on investigating the effects of training on FC start or turn performance. The impact of resistance on FC velocity Clusters #1 and #8 (Fig. 4) focus on resistance in swimming. Resistance refers to the force that opposes the forward motion of swimmers in the water and is influenced by various factors, including swimming posture, water density, viscosity, velocity, and flow patterns. Resistance was first obtained when measuring adult swimming[ 39 ]. Resistance can be categorized into active resistance and passive resistance (Kolmogorov and Duplishcheva, 1992). Active resistance is the resistance generated by swimmers themselves through their movements and postures, such as arm and leg strokes, body posture, and breathing patterns[ 40 ]. Studies have shown that active resistance experienced by the body during swimming is generally 1.5 to 2 times greater than passive resistance[ 40 ]. Furthermore, research has consistently demonstrated that swimmers with better technique generate lower resistance coefficients. Elite swimmers typically experience less resistance than non-elite swimmers[ 39 ]. Additionally, higher-level swimmers often exhibit greater resistance and resistance coefficients[ 41 – 49 ]. This could be attributed to factors such as the swimmer's velocity and projected frontal surface area[ 2 ]. Swimmers with larger body sizes are more likely to experience greater resistance[ 42 , 48 , 50 ], and as athletes age and their body size increases, their resistance during swimming also tends to increase[ 48 ]. However, technical training plays a crucial role in reducing resistance. A study by Neiva et al. (2021) showed that after 4 weeks of aerobic training, elite swimmers experienced a decrease in resistance and an improvement in FC performance[ 51 ]. This highlights the importance of technical training in addressing and minimizing resistance. Breathing also affects the resistance experienced by swimmers. Research has indicated that swimming with breathing leads to a higher resistance than swimming without breathing, with the resistance increase ranging from 16–26%[ 52 ]. It is worth noting that while an increase in resistance is generally considered detrimental to performance, there are instances, particularly in short-distance swimming, where higher resistance is associated with faster swimming speeds and better swimming efficiency[ 53 , 54 ]. Therefore, the relationship between resistance and performance is complex, and simply reducing resistance may not always lead to improved performance. Overall, understanding and addressing resistance in swimming are crucial for swimmers and coaches aiming to optimize performance. Technical training, body positioning, and breathing techniques are important factors to consider in managing and minimizing resistance during swimming. The application of Inertial Measurement Units in FC Clusters #5, #6, #7 and #10 (Fig. 4) focus on the applications of inertial sensor technology, specifically Inertial Measurement Units (IMUs), in swimming analysis and training. IMUs, consisting of accelerometers and gyroscopes, provide valuable data on the movement of different body parts, enabling researchers to analyze and study kinematic characteristics and changes in the body's center of mass with greater accuracy. In swimming, IMUs have gained significant attention as a valuable tool for monitoring and improving training. Ohgi et al. (2000) were among the first to analyze FC using IMUs. They developed a dual-axis accelerometer sensor and studied the relationship between wrist acceleration data and arm movements[ 55 ]. Guignard et al. (2021) validated the effectiveness, reliability, and accuracy of IMUs in swimming analysis, suggesting that they should be considered a feasible choice for capturing swimming systems[ 56 ]. Caporaso et al. (2020) found a strong correlation between performance indices obtained from IMU-based and camera-based methods[ 57 ]. Compared to 2D video capture and 3D infrared camera systems, IMUs are a viable option for evaluating FC arm stroking[ 58 ]. The importance of IMUs as a tool for assessing the arm propulsion phase in swimming has been emphasized by Cortesi et al. (2019)[ 59 ]. IMU-based sensor systems have also been utilized for swimming stroke classification and motion analysis[ 60 ]. In addition to arm movements, IMUs can be used to predict the number of leg kicks performed by triathletes during FC competitions[ 61 ]. Fulton et al. (2009) quantitatively analyzed leg kick count and frequency in 100-meter FC for 14 Paralympic swimmers using IMUs[ 62 ]. Their results demonstrated that increasing kicking frequency can improve FC performance. Furthermore, Fulton, Pyne, and Burkett (2011) quantified kicking frequency in 12 Paralympic athletes and determined the optimal combination of kick frequency and amplitude[ 63 ]. IMUs can determine absolute speed[ 64 ]and instantaneous speed[ 65 ] in FC. They can also provide stroke technique analysis throughout the stroke cycle[ 66 ], estimate energy expenditure[ 67 ], and assess propulsive force[ 68 ] during FC. Overall, IMUs have shown great potential in swimming analysis and training. Their ability to capture and analyze various aspects of swimming performance, including arm movements, leg kicks, speed, stroke technique, energy expenditure, and propulsive force, makes them valuable tools for swimmers, coaches, and researchers seeking to enhance swimming performance and technique. In the study conducted by Callaway et al. (2015), multiple IMUs were utilized to calculate various parameters in FC, encompassing lap time, speed, stroke count, stroke duration, stroke frequency, and stroke phase[ 69 ]. Furthermore, Demarie et al. (2023) assessed upper limb asymmetry among elite and young male and female swimmers by capturing acceleration data using IMUs[ 70 ]. Additionally, Regaieg et al. (2023) demonstrated the capability of accurately quantifying upper limb coordination asymmetry in swimmers with physical impairments by utilizing IMUs[ 71 ]. Consequently, it is recommended that future researchers delve into further exploration of the application of inertial sensor technology in swimming, with a focus on investigating its potential and scope, as well as integrating it with other technologies and methodologies to offer comprehensive support and guidance for swimmers’ training and performance. 5 Conclusion Based on the results obtained from CiteSpace, this study identified the significant authors and journals in the field of FC biomechanics. Through analyzing keyword co-occurrence, keyword cluster, and burst term, we determined the research hotspots, frontiers, and trends in the FC biomechanics. This study makes several contributions. Firstly, from a temporal perspective, it offers extensive insights into the hotspots, trends, and frontiers in FC biomechanics. Visualizing the literature through graphs and explicit methods enables researchers to track and monitor research progress. Secondly, it presents a comprehensive network map and information table of FC biomechanics research, providing clear guidance for monitoring developments and identifying emerging trends. Thirdly, it highlights the discipline's most influential authors, institutions, countries, and journals, facilitating precise searches on authors and journals. Lastly, it guides using CiteSpace for knowledge mapping in FC biomechanics. However, this study has some limitations. Firstly, the dataset only includes English articles, potentially excluding relevant research published in other languages. Secondly, the sample is limited to journal articles indexed in Web of Science, which may only cover some relevant journals in the field. Additionally, the specific keywords and search strings used in the literature search may restrict the dataset, potentially omitting authors who explore FC biomechanics without explicitly mentioning it. Lastly, the dataset is limited to articles and review papers, which may only partially represent some available literature in FC biomechanics. Future research could expand the data collection to include other publication types for a more comprehensive understanding of the latest research findings in FC biomechanics. Declarations Acknowledgments Not applicable. Author contributions DX and DHKC designed the research. DX and KY collected the data. DX, KY, and DHKC processed the data. DX and DHKC wrote the paper. All authors read and approved the final manuscript. Funding This research was funded by the Chinese Ministry of Education's Collaborative Education Program for Industry-University Cooperation (NO. 230722482207213). Availability of data and materials All the data used to support the findings of this study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate Not applicable. Consent for publication The authors declare that they consent to publication. Competing interests The authors declare that they have no conflicts of interest. 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In 2020 IEEE International Workshop on Metrology for Industry 40 & IoT . IEEE; 2020:116–120. Lee JB, Burkett BJ, Thiel D, James DJPE: Inertial sensor, 3D and 2D assessment of stroke phases in freestyle swimming. 2011, 13:148–153 Cortesi M, Giovanardi A, Gatta G, Mangia AL, Bartolomei S, Fantozzi SJJoSS, Medicine: Inertial sensors in swimming: Detection of stroke phases through 3D wrist trajectory. 2019, 18(3):438 Zhang Z, Xu D, Zhou Z, Mai J, He Z, Wang Q: IMU-based underwater sensing system for swimming stroke classification and motion analysis. In 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS) . IEEE; 2017:268–272. Bianchi V, Ambrosini L, Presta V, Gobbi G, De Munari IJAS: Prediction of Kick Count in Triathletes during Freestyle Swimming Session Using Inertial Sensor Technology. 2022, 12(13):6313 Fulton SK, Pyne DB, Burkett BJJoss: Quantifying freestyle kick-count and kick-rate patterns in Paralympic swimming. 2009, 27(13):1455–1461 Fulton SK, Pyne D, Burkett BJJoSS: Optimizing kick rate and amplitude for Paralympic swimmers via net force measures. 2011, 29(4):381–387 Stamm A, Thiel DV, Burkett B, James DAJPE: Towards determining absolute velocity of freestyle swimming using 3-axis accelerometers. 2011, 13:120–125 Dadashi F, Crettenand F, Millet GP, Aminian KJS: Front-crawl instantaneous velocity estimation using a wearable inertial measurement unit. 2012, 12(10):12927–12939 Engel A, Schaffert N, Ploigt R, Mattes K: Intra-cyclic analysis of the front crawl swimming technique with an inertial measurement unit. 2022 Dadashi F, Millet GP, Aminian KJISJ: Estimation of front-crawl energy expenditure using wearable inertial measurement units. 2013, 14(4):1020–1027 Kadi T, Wada T, Narita K, Tsunokawa T, Mankyu H, Tamaki H, Ogita FJS: Novel Method for Estimating Propulsive Force Generated by Swimmers’ Hands Using Inertial Measurement Units and Pressure Sensors. 2022, 22(17):6695 Callaway AJJS: Measuring kinematic variables in front crawl swimming using accelerometers: A validation study. 2015, 15(5):11363–11386 Demarie S, Guidotti F, Minganti C, Passerini A, Nagni GJMdS: Technique and coordination of the front crawl swimming stroke. 2023, 76(3):299–309 Regaieg MA, Létocart AJ, Bosche J, Seifert L, Guignard BJISJ: Automatic Detection of Key Points of the Cycle to Assess Upper-Limb Coordination in Front Crawl: Effect of Swimming Speed and Impairment. 2023 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4023457","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277215809,"identity":"b70260fa-fc7f-47d1-a22e-bf5f02568508","order_by":0,"name":"Dongxiang HUANG","email":"","orcid":"","institution":"Shaoguan University","correspondingAuthor":false,"prefix":"","firstName":"Dongxiang","middleName":"","lastName":"HUANG","suffix":""},{"id":277215810,"identity":"81a34d36-6d79-4a52-88c8-6b5666b19e65","order_by":1,"name":"Keyi ZHANG","email":"","orcid":"","institution":"The Education University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Keyi","middleName":"","lastName":"ZHANG","suffix":""},{"id":277215812,"identity":"d0348a02-f7b8-4804-a31d-73b951e6cb11","order_by":2,"name":"Huang Kay CHOW","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYDCCAyBUwJDAwMB8gIGH4YABgwQbMVoMQFrYEojXwgDRwmNAnBa+42cPHvhgYJfHL5Hz8cHbtjvGDNJtCXi1SJ7JSzg4wyC5WHJG7mbDuW3PzBhkjh3Aq8XgQI7BYR6DA4kbbuduk+ZtO2zDIJHegF/L+TcGh/+AteQ8/02clhtAWxggWtiYgVrMGCTS8DtM8sYbg4M9BsmJM+c/M5acc+6wMZtEWgJeLXznc4w//KiwS+znOfzww5uyw4b9EmkGeLVgAkIROQpGwSgYBaOACAAAdOFRiyjavNcAAAAASUVORK5CYII=","orcid":"","institution":"The Education University of Hong Kong","correspondingAuthor":true,"prefix":"","firstName":"Huang","middleName":"Kay","lastName":"CHOW","suffix":""}],"badges":[],"createdAt":"2024-03-07 08:00:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4023457/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4023457/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52525522,"identity":"535f1608-da83-45c6-a8cf-e610ad4b9eb0","added_by":"auto","created_at":"2024-03-12 15:49:07","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47575,"visible":true,"origin":"","legend":"\u003cp\u003eThe annual number of publications from 1984 to 2023\u003c/p\u003e","description":"","filename":"Slide1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4023457/v1/f086157946eebfc6e6d6574e.jpg"},{"id":52525524,"identity":"bbe62521-c904-4fba-9f01-c3d9461e26f5","added_by":"auto","created_at":"2024-03-12 15:49:07","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":94145,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurrence analysis of Keywords\u003c/p\u003e","description":"","filename":"Slide2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4023457/v1/dcaff467bc3fe32468fd70d5.jpg"},{"id":52525523,"identity":"82b663fe-07ad-4eb0-9c33-b2e40ce58e10","added_by":"auto","created_at":"2024-03-12 15:49:07","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":59328,"visible":true,"origin":"","legend":"\u003cp\u003eTop 8 keywords in burst impact\u003c/p\u003e","description":"","filename":"Slide3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4023457/v1/d8efcb5e4fb2490276d6664a.jpg"},{"id":52525525,"identity":"a7795792-2ae5-4de5-8748-46490282308d","added_by":"auto","created_at":"2024-03-12 15:49:07","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":95629,"visible":true,"origin":"","legend":"\u003cp\u003eCluster map of keywords\u003c/p\u003e","description":"","filename":"Slide4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4023457/v1/4eddc57b0c9620d912babad5.jpg"},{"id":52545467,"identity":"51f86d68-6e57-47e9-a474-6e12e2a02ffe","added_by":"auto","created_at":"2024-03-12 18:21:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":593041,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4023457/v1/d731b138-bcf8-4fd4-b845-b808cf403575.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive bibliometric and visualized analysis of research on front crawl biomechanics published from 1984 to 2023","fulltext":[{"header":"1. Background","content":"\u003cp\u003eCompetitive swimming comprises four swimming styles: front crawl (FC) swimming, backstroke, breaststroke, and butterfly. Among these, FC is recognized for its minimal resistance, high speed, and reduced effort compared to other strokes[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the Olympic Games, there are 32 swimming events, with 13 dedicated to FC. Additionally, FC is incorporated into medley and medley relay events. Consequently, FC is a significant indicator o\u003cem\u003ef a country's competitive swimming strength\u003c/em\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. \u003cem\u003eNumerous countries and research institutions focus on enhancing FC techniques, and the field of sports biomechanics has provided a scientific foundati\u003c/em\u003eon for such improvements[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Sports biomechanics examines athletes' mechanical characteristics and control mechanisms during exercise[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. It facilitates a deeper understanding of swimmers' movement techniques, power output, and dynamic characteristics, optimizing training methods, improving sports performance, and preventing sports injuries[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Consequently, many scholars have taken a keen interest in studying FC biomechanics. While significant research findings have emerged in this field over the last 39 years, there remains a need for systematic analysis and evaluation of the existing literature.\u003c/p\u003e \u003cp\u003eBibliometric review, a systematic analysis and measurement approach for scientific research literature[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], offers insights into the development trends, impact, quality, relationships, and emerging themes among different publications [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], by collecting, organizing, and analyzing relevant literature data, a bibliometric review helps overcome the subjective biases of narrative literature reviews[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Citespace, a bibliometric tool, constructs network maps of scientific literature to uncover citation relationships, thematic evolution, and research frontiers[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, this study employs Citespace software to provide a comprehensive overview of the research history in FC biomechanics based on a thorough analysis of research achievements over the last 39 years. This study aims to identify the structure, dynamic evolution patterns, and trends within this field and offer valuable insights for future scholars investigating FC biomechanics.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data Collection\u003c/h2\u003e \u003cp\u003eThe database for this study consists of data acquired from the SCI-Expanded, SSCI, CPCI-S, and CPCI-SSH databases within the Web of Science\u0026trade; Core Collection. To collect the relevant literature, Boolean operators (AND, OR) were applied to combine keywords. The initial searches were conducted using the following terms: #1: TS = (Biomechanic* OR Kinematic* OR Kinetic* OR \u0026lsquo;Force plate\u0026rsquo; OR \u0026lsquo;force platform\u0026rsquo; OR \u0026lsquo;Motion capture\u0026rsquo; OR EMG OR Electromyography OR \u0026lsquo;Muscle activation\u0026rsquo; OR Hydrodynamic* OR mechanic*), #2: TS = (\u0026lsquo;Front crawl\u0026rsquo; OR FC OR Freestyle), and #3: TS = (Swim OR Swimming). These searches yielded 3,666,042, 3,252, and 75,674 retrieved records, respectively. Subsequently, a combined search was performed using #1 AND #2 AND #3. The search results were refined to include only \u0026lsquo;Article\u0026rsquo; and \u0026lsquo;Review Article\u0026rsquo; document types and were restricted to the English language. Articles that did not align with the subject of FC biomechanics were excluded. Ultimately, 508 relevant articles were obtained and utilized as the research data for this study. The search was conducted up to December 31, 2023, ensuring the inclusion of the most recent literature available.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Research tool\u003c/h2\u003e \u003cp\u003eIn this study, the Java-based software program called Citespace (version 6.2.R3) was utilized to visually analyze the field of FC biomechanics. Citespace allows for the extraction and reorganization of author, institution, country, and keyword information from literature, facilitating the visualization of analytical results. By employing Citespace, precise tracking, and analysis of frontier trends and the dynamic evolution of research fields in FC biomechanics were made possible[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Parameter setting\u003c/h2\u003e \u003cp\u003eThe parameters were set as follows: Time slicing: each year as a time slice from 1984 to 2023; Term source: title, abstract, author keywords, and keywords plus; Node types: author, Journal, keywords; Selection criteria: \"g-index\u0026thinsp;=\u0026thinsp;25\" for author, Journal, \"g-index\u0026thinsp;=\u0026thinsp;10\" for Keywords; and Pruning options: Pathfinder, pruning the merged network.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 General information\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eAnnual Publication Analysis\u003c/strong\u003e \u003cp\u003eThe trend in annual publications of core papers in the study of FC biomechanics over the past 39 years is depicted (Fig.\u0026nbsp;1). It can be observed that the first paper in this field was published in 1984, and there has been a steady increase in the number of annual publications in the field, with slight fluctuations.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;1\u003c/b\u003e The annual number of publications from 1984 to 2023.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAuthor Analysis\u003c/strong\u003e \u003cp\u003eAs depicted in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the authors in the field of FC biomechanics, aside from, Ricardo J. Fernandes, are Tiago M. Barbosa, Daniel A. Marinho, Jo\u0026atilde;o Paulo Vilas-boas, and Jorge E. Morais, all of whom have a publication volume exceeding 30 articles. Furthermore, they all exhibit high centrality rankings, with Ricardo J. Fernandes maintaining the first position, Joao Paulo Vilas-boas ranking second, and Tiago M. Barbosa ranking third.\u003c/p\u003e \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\u003eTop 10 authors with the highest publications and centrality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHigh publications author\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHigh centrality author\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCentrality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFernandes, Ricardo J\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFernandes, Ricardo J\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBarbosa, Tiago M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVilas-boas, Joao Paulo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarinho, Daniel A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBarbosa, Tiago M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVilas-boas, Joao Paulo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSeifert, Ludovic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMorais, Jorge E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChollet, Didier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFigueiredo, Pedro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHellard, P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeifert, Ludovic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMarinho, Daniel A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChollet, Didier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSanders, Ross H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSanders, Ross H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGonjo, Tomohiro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta, Mario J\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTakagi, Hideki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\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 \u003cstrong\u003eJournal Analysis\u003c/strong\u003e \u003cp\u003eThe information on the top 10 cited journals is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The most significant number of citations, as well as the highest centrality, were observed in the International Journal of Sports Medicine.\u003c/p\u003e \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\u003eTop 10 cited journals and the importance index (centrality value)\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=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCentrality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePublishing Country/Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInternational Journal of Sports Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Sports Sciences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedicine and Science in Sports and Exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Biomechanics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEuropean Journal of Applied Physiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Applied Biomechanics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSports Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNew Zealand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Strength and Conditioning Research\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman Movement Science\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Science and Medicine in Sport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\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\u003e3.2 Keyword co-occurrence analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe 508 articles were imported into Citespace, with the \"time slice length\" set to 1. The selection criteria used were K\u0026thinsp;=\u0026thinsp;10, LRF\u0026thinsp;=\u0026thinsp;3.0, L/N\u0026thinsp;=\u0026thinsp;10, LBY\u0026thinsp;=\u0026thinsp;5, and e\u0026thinsp;=\u0026thinsp;1.0, and the Pathfinder strategy was applied, resulting in the acquisition of a keyword co-occurrence map for FC biomechanics research, which comprised 264 nodes and 523 links (Fig.\u0026nbsp;2). The top 10 keywords in terms of frequency and centrality are presented in Table\u0026nbsp;4. It is observed from Fig.\u0026nbsp;6 and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e that front crawl exhibits the highest frequency of occurrence. Notably, although keywords such as biomechanics, active drag, and efficiency do not appear in the top 10 in terms of frequency, their centrality is relatively high.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;2\u003c/b\u003e Co-occurrence analysis of Keywords\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\u003eTop 10 Keywords with the highest publications and centrality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHigh-frequency keywords\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHigh centrality keywords\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeywords\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKeywords\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCentrality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efront crawl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ebiomechanics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evelocity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eexercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eperformance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eactive drag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eswimmers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eswimmers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edistance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eefficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eparameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003efront crawl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eexercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eenergetics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003earm coordination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecompetitive swimming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edrag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecoordination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eenergy cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003edrag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\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\u003eAn analysis of burst terms in the field of FC biomechanics was conducted based on keyword co-occurrence. The burst terms map (Fig.\u0026nbsp;3) was obtained and arranged in ascending order of time. It was observed that the time periods of keyword emergence were not independent; there was a cross-overlap in time, and the content was carried forward and backwards.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;3\u003c/b\u003e Top 8 keywords in burst impact\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Cluster analysis\u003c/h2\u003e \u003cp\u003eUsing the log-likelihood algorithm (LLR), a cluster analysis was conducted on the keywords in the field of FC biomechanics based on the method of keyword co-occurrence. This analysis produced a cluster map comprising 264 nodes and 523 links (Fig.\u0026nbsp;4). The figure exhibits a Q value of 0.722 and an S value of 0.8657, of visually representing the top 11 clusters.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;4\u003c/b\u003e Cluster map of keywords\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.1 General information\u003c/h2\u003e \u003cp\u003eThe number of publications and the changing trends in annual publication quantities indicate the overall significance and evolving interests of scholars in a particular field[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The annual publication rate in the field of FC biomechanics has exhibited a steady increase with minor fluctuations. Before 2008, the number of publications in this field could have been higher, with fewer than ten articles. This initial stage can be considered as the early phase of research. Scholars' attention towards FC biomechanics has continued to grow since 2008, resulting in a peak in the number of publications in 2023. During this period, researchers have shown a high level of enthusiasm for studying FC biomechanics, actively publishing articles, and promoting the development of the field. This can be regarded as the peak period of research. Based on the publication trend line, it can be inferred that the annual publication rate is expected to continue increasing in the future, reflecting the ongoing development and advancement of research in this field.\u003c/p\u003e \u003cp\u003eCentrality, as defined by Chen (2006), measures an author's significance and impact within a network[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Authors with high centrality indicate their importance and influence within the collaborative network. In this regard, Ricardo J. Fernandes Joao Paulo Vilas-boas Tiago M. Barbosa Ludovic Seifert Didier Chollet Daniel A. Marinho Ross H. Sanders not only demonstrate a substantial number of publications but also exhibit a considerable value of centrality. This suggests that they hold notable influence and standing within the academic field. It is noteworthy that Hellard, P, Gonjo, Tomohiro, and Hideki, Takagi while not ranking within the top 10 list in terms of publication count, possess relatively high centrality. This implies that they also hold significant influence and importance within the field of FC biomechanics. These findings provide valuable insights for future scholars, offering information on key authors in the field of FC biomechanics.\u003c/p\u003e \u003cp\u003eThe citation count of INT J SPORTS MED, J SPORT SCI, MED SCI SPORT EXER, and J BIOMECH, all exceeding 300, indicates that their published research findings have a high impact and recognition in FC biomechanics. These journals are widely acknowledged by other researchers and are considered to have high research quality and academic value. In the analysis of journal citations, high centrality represents the importance of the journal[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. INT J SPORTS MED, in addition to having a large number of citations, also has high centrality, indicating its significant position and extensive collaborative relationships in FC biomechanics. This suggests that the journal is crucial in disseminating research and fostering collaborations within the field. Future researchers can delve into FC biomechanics by collecting papers from these top journals to explore the latest research findings, methodologies, and advancements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Hotspots and Frontiers\u003c/h2\u003e \u003cp\u003eFrom an epistemological standpoint, keywords with high frequency and centrality often signify topics researchers collectively emphasize during a specific period, signifying research novelty and frontiers[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Citespace assesses the proximity among a set of keywords by tallying their co-occurrence frequency in the literature, thereby facilitating the identification of research hotspots within specific disciplines[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In FC biomechanics, the term \u0026lsquo;front crawl\u0026rsquo; exhibits the highest frequency, appearing 159 times, as it\u0026rsquo;s the term we used in the literature search. Keywords such as \u0026lsquo;velocity\u0026rsquo; and \u0026lsquo;performance\u0026rsquo; surpass 100 occurrences, alongside \u0026lsquo;swimmers,\u0026rsquo; \u0026lsquo;distance,\u0026rsquo; \u0026lsquo;parameters,\u0026rsquo; and \u0026lsquo;exercise,\u0026rsquo; which have guided the research trajectory in FC biomechanics over the past 39 years.\u003c/p\u003e \u003cp\u003eKeywords with centrality exceeding 0.01 indicate extensive research activity and heightened impact[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Notably, keywords such as \u0026lsquo;biomechanics,\u0026rsquo; \u0026lsquo;exercise,\u0026rsquo; \u0026lsquo;active drag,\u0026rsquo; and \u0026lsquo;swimmers\u0026rsquo; possess centrality values surpassing 0.1, underscoring their substantial influence and role as focal points in FC biomechanics research.\u003c/p\u003e \u003cp\u003eHigh-frequency keywords reveal researchers\u0026rsquo; profound interest in fundamental characteristics and FC performance. Keywords of high centrality highlight researchers\u0026rsquo; focus on optimizing FC performance and enhancing swimming efficiency, particularly through the exploration of biomechanical characteristics, training methodologies, and energy expenditure in FC.\u003c/p\u003e \u003cp\u003eUnder the definition provided in previous research, frontier research pertains to a collection of emerging and dynamic concepts along with potential research questions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It accentuates novel trends and emerging features, representing a central topic that a body of literature, characterized by burst terms, focuses on during a specific time period. Burst terms are keywords that experience a substantial increase in frequency within a delimited timeframe, signifying emerging research directions and significant advancements in the field[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. According to Fig.\u0026nbsp;7, the burst keywords in the field of FC biomechanics have undergone the evolutionary process of the budding stage (1999\u0026ndash;2015), the active exploration stage (2016\u0026ndash;2021), and the deepening advancement stage (2022\u0026ndash;2024). In the budding stage, the burst keywords include \"Body roll,\" \"stoking characteristics,\" \"motor control,\" and \"arm coordination.\" In the active exploration stage, the emerging keywords are \"acceleration,\" \"power,\" and \"kinetics.\" The emerging keywords in the deepening advancement stage include \"sprint\" and \"reliability.\"\u003c/p\u003e \u003cp\u003eDuring the budding stage, burst terms encompassed \u0026lsquo;Body roll,\u0026rsquo; \u0026lsquo;stroking characteristics,\u0026rsquo; \u0026lsquo;motor control,\u0026rsquo; and \u0026lsquo;arm coordination.\u0026rsquo; In the active exploration stage, burst terms included \u0026lsquo;acceleration,\u0026rsquo; \u0026lsquo;power,\u0026rsquo; and \u0026lsquo;kinetics.\u0026rsquo; Lastly, burst terms comprised \u0026lsquo;sprint\u0026rsquo; and \u0026lsquo;reliability\u0026rsquo; in the deepening advancement stage. Initially, researchers primarily concentrated on swimmers' fundamental movement characteristics and technical elements. Establishing a comprehensive understanding of these foundational aspects is a basis for subsequent research in FC biomechanics.\u003c/p\u003e \u003cp\u003eAs researchers introduced advanced equipment and delved deeper into the field, their focus expanded to areas such as motor control, power output, and dynamics. Subsequently, scholars directed their attention towards sprint swimming, validating research data, and ensuring the reliability of research equipment and data. This progression reflects researchers' unwavering pursuit of meticulousness and comprehensiveness. The field of FC biomechanics embodies a progressive accumulation of knowledge. Through continuous research achievements, scholars have propelled the development of FC biomechanics from focusing on basic techniques to exploring complex issues and validating data reliability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Research trend\u003c/h2\u003e \u003cp\u003eDifferent clusters of keywords can be formed by analyzing the high-frequency keywords used in the article, each representing a specific theme. This method can assist researchers in quickly understanding the research dynamics and trends in the field[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The Q value of 0.722 in Fig.\u0026nbsp;8 indicates a significant clustering structure, as it is greater than 0.3[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, the S value of 0.8657, which is greater than 0.5, suggests the high credibility of the clustering. By analyzing the cluster (Fig.\u0026nbsp;8) and interpreting the references associated with these clusters, we have identified four main research trends in the field of FC biomechanics:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRelationship between body rotation and FC performance\u003c/strong\u003e \u003cp\u003eIn FC, swimmers generate forward propulsion by employing alternating arm strokes. This process involves rotational movement of the trunk along the body's longitudinal axis, commonly referred to as body rotation. Body rotation control is regulated by the motor control system, which modulates muscle contraction and relaxation. The magnitude and direction of the principal moment of inertia influence the stability and control of body rotation. Consequently, this topic encompasses clusters #2, #9, #0, and #10 (Fig.\u0026nbsp;4).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe relationship between body rotation and FC performance has garnered considerable scholarly attention. For instance, Hay et al. (1993) were pioneers in utilizing computer simulation models to simulate FC movements[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Their research revealed that body rotation can lead to deviation of the hands towards the body's midline during the pull phase, thereby impacting stroke technique. Building upon Hay's work, Payton et al. (1997) further explored the influence of body rotation on arm stroke velocity and trajectory[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The findings demonstrated that increased body rotation significantly affected hand trajectory and enhanced stroke velocity, thereby enhancing propulsion.\u003c/p\u003e \u003cp\u003eFurthermore, studies have examined differences in body rotation between breathing and non-breathing conditions using videography. For example, Payton et al. (1999) discovered that swimmers exhibited larger body rotation angles during breathing (66\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u0026deg;) compared to non-breathing conditions (57\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u0026deg;)[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. De Souza Castro et al. (2007) reported that most swimmers demonstrated increased body rotation during breathing, whereas triathletes displayed no significant variation in body rotation between breathing and non-breathing conditions[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese studies often treat body rotation as a unified concept, disregarding the distinct contributions of shoulder and hip rotation. Research has revealed variations in the magnitude and timing of shoulder rotation and hip rotation among different swimmers and even between the left and right sides of the same swimmer[\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Consequently, to gain a more comprehensive understanding of the movement characteristics of body rotation, it is imperative to analyze the rotation of the shoulders and hips separately. This approach would yield more detailed outcomes and enable readers to comprehend better the underlying mechanisms governing body rotation underlying mechanisms.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eThe impact of training on biomechanical parameters in FC\u003c/strong\u003e \u003cp\u003eThis topic encompasses clusters #3, #4, and #10 (Fig.\u0026nbsp;4). Training methods commonly employed in swimming include strength training, resistance training, core training, and others. These training modalities have been shown to enhance athletes' muscle strength, swimming efficiency, body stability, and muscle explosiveness, consequently leading to improved FC performance[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/p\u003e \u003cp\u003eIn swimming, time is a critical performance indicator, with velocity being a primary determinant of time. Stroke rate and length are crucial factors influencing swimming velocity and positively contribute to overall swimming performance[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Increasing stroke rate and length can enhance velocity[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] as velocity is the product of stroke rate and length[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, numerous studies evaluate the impact of training on FC performance by measuring stroke rate and length.\u003c/p\u003e \u003cp\u003eFor instance, research has demonstrated that resistance training or core training can improve stroke length[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Girold et al. (2012) found that strength training has a maximal positive effect on enhancing stroke length[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This can be attributed to the fact that increasing stroke length necessitates swimmers to possess higher muscle strength to exert greater force and overcome water resistance[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Thus, after several weeks of strength training, swimmers' muscle strength improves, resulting in positive advancements in stroke length.\u003c/p\u003e \u003cp\u003eHowever, the findings of studies by Gourgoulis et al. (2019) and Karpiński et al. (2020) indicated that strength or resistance training led to improved stroke rate but decreased stroke length[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. While an increase in stroke rate typically corresponds to a decrease in stroke length, training can still enhance FC performance through strength and resistance training[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Crowley et al. (2017) highlighted in their research report that most training exerts a greater influence on stroke rate than stroke length, particularly after several weeks of strength and endurance training, where the impact on stroke rate becomes more significant[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The stroke rate is crucial for maximizing velocity[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, further research is needed to determine the optimal balance between stroke rate and length for improved FC performance.\u003c/p\u003e \u003cp\u003eElastic training has been shown to positively impact maximal lower limb strength and explosiveness[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], making it highly valued in swimming training. Studies have demonstrated that elastic training is crucial for optimizing FC start performance[\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Elastic training enhances joint torque in the lower limbs and enables control of the resultant force vector direction, thereby improving FC start performance[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Rejman et al. (2017) established that elastic training enhances average speed during the take-off, flight, and glide phases, resulting in reduced start time and optimized FC start performance[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, investigations have examined the impact of core muscle training on FC turn performance. Karpiński et al. (2020) demonstrated that six weeks of core muscle training significantly reduced the time for the 5-meter section after the turn and improved the average speed for the same section[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Start and turn play a crucial role in FC performance. However, there is currently a dearth of research concerning the effects of training on the biomechanics of FC start or turn. Thus, future research could focus on investigating the effects of training on FC start or turn performance.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eThe impact of resistance on FC velocity\u003c/strong\u003e \u003cp\u003eClusters #1 and #8 (Fig.\u0026nbsp;4) focus on resistance in swimming. Resistance refers to the force that opposes the forward motion of swimmers in the water and is influenced by various factors, including swimming posture, water density, viscosity, velocity, and flow patterns.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eResistance was first obtained when measuring adult swimming[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Resistance can be categorized into active resistance and passive resistance (Kolmogorov and Duplishcheva, 1992). Active resistance is the resistance generated by swimmers themselves through their movements and postures, such as arm and leg strokes, body posture, and breathing patterns[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies have shown that active resistance experienced by the body during swimming is generally 1.5 to 2 times greater than passive resistance[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Furthermore, research has consistently demonstrated that swimmers with better technique generate lower resistance coefficients. Elite swimmers typically experience less resistance than non-elite swimmers[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Additionally, higher-level swimmers often exhibit greater resistance and resistance coefficients[\u003cspan additionalcitationids=\"CR42 CR43 CR44 CR45 CR46 CR47 CR48\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This could be attributed to factors such as the swimmer's velocity and projected frontal surface area[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Swimmers with larger body sizes are more likely to experience greater resistance[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], and as athletes age and their body size increases, their resistance during swimming also tends to increase[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. However, technical training plays a crucial role in reducing resistance. A study by Neiva et al. (2021) showed that after 4 weeks of aerobic training, elite swimmers experienced a decrease in resistance and an improvement in FC performance[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. This highlights the importance of technical training in addressing and minimizing resistance.\u003c/p\u003e \u003cp\u003eBreathing also affects the resistance experienced by swimmers. Research has indicated that swimming with breathing leads to a higher resistance than swimming without breathing, with the resistance increase ranging from 16\u0026ndash;26%[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is worth noting that while an increase in resistance is generally considered detrimental to performance, there are instances, particularly in short-distance swimming, where higher resistance is associated with faster swimming speeds and better swimming efficiency[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Therefore, the relationship between resistance and performance is complex, and simply reducing resistance may not always lead to improved performance.\u003c/p\u003e \u003cp\u003eOverall, understanding and addressing resistance in swimming are crucial for swimmers and coaches aiming to optimize performance. Technical training, body positioning, and breathing techniques are important factors to consider in managing and minimizing resistance during swimming.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eThe application of Inertial Measurement Units in FC\u003c/strong\u003e \u003cp\u003eClusters #5, #6, #7 and #10 (Fig.\u0026nbsp;4) focus on the applications of inertial sensor technology, specifically Inertial Measurement Units (IMUs), in swimming analysis and training. IMUs, consisting of accelerometers and gyroscopes, provide valuable data on the movement of different body parts, enabling researchers to analyze and study kinematic characteristics and changes in the body's center of mass with greater accuracy.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eIn swimming, IMUs have gained significant attention as a valuable tool for monitoring and improving training. Ohgi et al. (2000) were among the first to analyze FC using IMUs. They developed a dual-axis accelerometer sensor and studied the relationship between wrist acceleration data and arm movements[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGuignard et al. (2021) validated the effectiveness, reliability, and accuracy of IMUs in swimming analysis, suggesting that they should be considered a feasible choice for capturing swimming systems[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Caporaso et al. (2020) found a strong correlation between performance indices obtained from IMU-based and camera-based methods[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Compared to 2D video capture and 3D infrared camera systems, IMUs are a viable option for evaluating FC arm stroking[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe importance of IMUs as a tool for assessing the arm propulsion phase in swimming has been emphasized by Cortesi et al. (2019)[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. IMU-based sensor systems have also been utilized for swimming stroke classification and motion analysis[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to arm movements, IMUs can be used to predict the number of leg kicks performed by triathletes during FC competitions[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Fulton et al. (2009) quantitatively analyzed leg kick count and frequency in 100-meter FC for 14 Paralympic swimmers using IMUs[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Their results demonstrated that increasing kicking frequency can improve FC performance. Furthermore, Fulton, Pyne, and Burkett (2011) quantified kicking frequency in 12 Paralympic athletes and determined the optimal combination of kick frequency and amplitude[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIMUs can determine absolute speed[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]and instantaneous speed[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] in FC. They can also provide stroke technique analysis throughout the stroke cycle[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], estimate energy expenditure[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], and assess propulsive force[\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] during FC.\u003c/p\u003e \u003cp\u003eOverall, IMUs have shown great potential in swimming analysis and training. Their ability to capture and analyze various aspects of swimming performance, including arm movements, leg kicks, speed, stroke technique, energy expenditure, and propulsive force, makes them valuable tools for swimmers, coaches, and researchers seeking to enhance swimming performance and technique.\u003c/p\u003e \u003cp\u003eIn the study conducted by Callaway et al. (2015), multiple IMUs were utilized to calculate various parameters in FC, encompassing lap time, speed, stroke count, stroke duration, stroke frequency, and stroke phase[\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Furthermore, Demarie et al. (2023) assessed upper limb asymmetry among elite and young male and female swimmers by capturing acceleration data using IMUs[\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Additionally, Regaieg et al. (2023) demonstrated the capability of accurately quantifying upper limb coordination asymmetry in swimmers with physical impairments by utilizing IMUs[\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Consequently, it is recommended that future researchers delve into further exploration of the application of inertial sensor technology in swimming, with a focus on investigating its potential and scope, as well as integrating it with other technologies and methodologies to offer comprehensive support and guidance for swimmers\u0026rsquo; training and performance.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eBased on the results obtained from CiteSpace, this study identified the significant authors and journals in the field of FC biomechanics. Through analyzing keyword co-occurrence, keyword cluster, and burst term, we determined the research hotspots, frontiers, and trends in the FC biomechanics.\u003c/p\u003e \u003cp\u003eThis study makes several contributions. Firstly, from a temporal perspective, it offers extensive insights into the hotspots, trends, and frontiers in FC biomechanics. Visualizing the literature through graphs and explicit methods enables researchers to track and monitor research progress. Secondly, it presents a comprehensive network map and information table of FC biomechanics research, providing clear guidance for monitoring developments and identifying emerging trends. Thirdly, it highlights the discipline's most influential authors, institutions, countries, and journals, facilitating precise searches on authors and journals. Lastly, it guides using CiteSpace for knowledge mapping in FC biomechanics.\u003c/p\u003e \u003cp\u003eHowever, this study has some limitations. Firstly, the dataset only includes English articles, potentially excluding relevant research published in other languages. Secondly, the sample is limited to journal articles indexed in Web of Science, which may only cover some relevant journals in the field. Additionally, the specific keywords and search strings used in the literature search may restrict the dataset, potentially omitting authors who explore FC biomechanics without explicitly mentioning it. Lastly, the dataset is limited to articles and review papers, which may only partially represent some available literature in FC biomechanics. Future research could expand the data collection to include other publication types for a more comprehensive understanding of the latest research findings in FC biomechanics.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\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\u003eDX and DHKC designed the research. DX and KY collected the data. DX, KY, and DHKC processed the data. DX and DHKC wrote the paper. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Chinese Ministry of Education\u0026apos;s Collaborative Education Program for Industry-University Cooperation (NO. 230722482207213).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data used to support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they consent to publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u0026emsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBarbosa TM, Fernandes RJ, Keskinen KL, Vilas-Boas JPJEjoap: The influence of stroke mechanics into energy cost of elite swimmers. 2008, 103:139\u0026ndash;149\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZamparo P, Cortesi M, Gatta GJEjoap: The energy cost of swimming and its determinants. 2020, 120:41\u0026ndash;66\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrewin CB, Hopkins WG, Pyne DBJJoss: Relationship between world-ranking and Olympic performance of swimmers. 2004, 22(4):339\u0026ndash;345\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKwok WY, So BCL, Tse DHT, Ng SSMJJoSS, Medicine: A systematic review and meta-analysis: 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performance: a longitudinal cluster analysis. 2021, 92(1):21\u0026ndash;33\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolmogorov S, Vorontsov A, Vilas-Boas JPJAS: Metabolic power, active drag, mechanical and propelling efficiency of elite swimmers at 100 meter events in different competitive swimming techniques. 2021, 11(18):8511\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilva AF, Figueiredo P, Ribeiro J, Alves F, Vilas-Boas JP, Seifert L, Fernandes RJJMC: Integrated analysis of young swimmers\u0026rsquo; sprint performance. 2019, 23(3):354\u0026ndash;364\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeiva HP, Fernandes RJ, Cardoso R, Marinho DA, Abraldes JAJIJoER, Health P: Monitoring master swimmers\u0026rsquo; performance and active drag evolution along a training mesocycle. 2021, 18(7):3569\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFormosa D, Sayers M, Burkett BJIjosm: The influence of the breathing action on net drag force production in front crawl swimming. 2014:1124\u0026ndash;1129\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbosa TM, Costa MJ, Morais JE, Morou\u0026ccedil;o P, Moreira M, Garrido ND, Marinho DA, Silva AJJHMS: Characterization of speed fluctuation and drag force in young swimmers: A gender comparison. 2013, 32(6):1214\u0026ndash;1225\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRibeiro J, Figueiredo P, Morais S, Alves F, Toussaint H, Vilas-Boas JP, Fernandes RJJJoss: Biomechanics, energetics and coordination during extreme swimming intensity: effect of performance level. 2017, 35(16):1614\u0026ndash;1621\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOhgi Y, Yasumura M, Ichikawa H, Miyaji CJES: Analysis of stroke technique using acceleration sensor IC in freestyle swimming. 2000, 250:503\u0026ndash;511\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuignard B, Ayad O, Baillet H, Mell F, Simbana Escobar D, Boulanger J, Seifert LJSB: Validity, reliability and accuracy of inertial measurement units (IMUs) to measure angles: application in swimming. 2021:1\u0026ndash;33\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaporaso T, Worsey M, Espinosa HG, Thiel DV, Palomba A, Grazioso S, Panariello D, Di Gironimo G, Lanzotti A: A preliminary approach for swimming performance analysis of fisdir elite athletes with intellectual impairment using an inertial sensor. In \u003cem\u003e2020 IEEE International Workshop on Metrology for Industry 40 \u0026amp; IoT\u003c/em\u003e. IEEE; 2020:116\u0026ndash;120.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee JB, Burkett BJ, Thiel D, James DJPE: Inertial sensor, 3D and 2D assessment of stroke phases in freestyle swimming. 2011, 13:148\u0026ndash;153\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCortesi M, Giovanardi A, Gatta G, Mangia AL, Bartolomei S, Fantozzi SJJoSS, Medicine: Inertial sensors in swimming: Detection of stroke phases through 3D wrist trajectory. 2019, 18(3):438\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Z, Xu D, Zhou Z, Mai J, He Z, Wang Q: IMU-based underwater sensing system for swimming stroke classification and motion analysis. In 2017 \u003cem\u003eIEEE International Conference on Cyborg and Bionic\u003c/em\u003e Systems \u003cem\u003e(CBS)\u003c/em\u003e. IEEE; 2017:268\u0026ndash;272.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBianchi V, Ambrosini L, Presta V, Gobbi G, De Munari IJAS: Prediction of Kick Count in Triathletes during Freestyle Swimming Session Using Inertial Sensor Technology. 2022, 12(13):6313\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFulton SK, Pyne DB, Burkett BJJoss: Quantifying freestyle kick-count and kick-rate patterns in Paralympic swimming. 2009, 27(13):1455\u0026ndash;1461\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFulton SK, Pyne D, Burkett BJJoSS: Optimizing kick rate and amplitude for Paralympic swimmers via net force measures. 2011, 29(4):381\u0026ndash;387\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStamm A, Thiel DV, Burkett B, James DAJPE: Towards determining absolute velocity of freestyle swimming using 3-axis accelerometers. 2011, 13:120\u0026ndash;125\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDadashi F, Crettenand F, Millet GP, Aminian KJS: Front-crawl instantaneous velocity estimation using a wearable inertial measurement unit. 2012, 12(10):12927\u0026ndash;12939\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEngel A, Schaffert N, Ploigt R, Mattes K: Intra-cyclic analysis of the front crawl swimming technique with an inertial measurement unit. 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDadashi F, Millet GP, Aminian KJISJ: Estimation of front-crawl energy expenditure using wearable inertial measurement units. 2013, 14(4):1020\u0026ndash;1027\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKadi T, Wada T, Narita K, Tsunokawa T, Mankyu H, Tamaki H, Ogita FJS: Novel Method for Estimating Propulsive Force Generated by Swimmers\u0026rsquo; Hands Using Inertial Measurement Units and Pressure Sensors. 2022, 22(17):6695\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCallaway AJJS: Measuring kinematic variables in front crawl swimming using accelerometers: A validation study. 2015, 15(5):11363\u0026ndash;11386\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemarie S, Guidotti F, Minganti C, Passerini A, Nagni GJMdS: Technique and coordination of the front crawl swimming stroke. 2023, 76(3):299\u0026ndash;309\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRegaieg MA, L\u0026eacute;tocart AJ, Bosche J, Seifert L, Guignard BJISJ: Automatic Detection of Key Points of the Cycle to Assess Upper-Limb Coordination in Front Crawl: Effect of Swimming Speed and Impairment. 2023\u003c/span\u003e\u003c/li\u003e\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":"Front Crawl Swimming, Sports Biomechanics, Citespace, Knowledge Domain","lastPublishedDoi":"10.21203/rs.3.rs-4023457/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4023457/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe biomechanical review of front crawl (FC) swimming can enhance athletes' technical proficiency and prevent sports injuries. Over the last 39 years, considerable research has been conducted on FC biomechanics. However, there exists a need for more bibliometrics studies. The objective of this study is to create a knowledge map highlighting the prominent research areas and cutting-edge frontiers in the field of FC biomechanics.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing Citespace, this study conducts bibliometric and visualization analysis of 508 articles in the field of FC biomechanics sourced from the Web of Science Core Collection database. The study focuses on collaboration networks among authors. Additionally, it examines the co-citation analysis of journals and performs co-occurrence, cluster, and burst term analysis on keywords.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eRicardo J. Fernandes is the most influential author. We found that the journal INT J SPORTS MED has been the most frequently cited publication. The popular keywords in this field include velocity, performance, and swimmers. Moreover, we identified several burst keywords, such as body roll, stroking characteristics, and motor control. Through cluster analysis, we identified that body roll, drag, motor control, and training are highly interconnected concepts in this domain.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe forefront of research in the field of FC biomechanics has evolved from a focus on fundamental techniques to addressing complex problems and, subsequently, validating research methods and data reliability. Future research directions may consider separately analyzing the impact of shoulder and hip rotation on freestyle performance, investigating the effects of training on freestyle starts or turns, and exploring the potential and application scope of inertial sensors. By integrating other technologies and methods, this research aims to provide comprehensive support and guidance for the training and performance of swimmers.\u003c/p\u003e","manuscriptTitle":"Comprehensive bibliometric and visualized analysis of research on front crawl biomechanics published from 1984 to 2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-12 15:49:02","doi":"10.21203/rs.3.rs-4023457/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":"70f1356f-4028-4c3d-9e43-e63ca8f37ffa","owner":[],"postedDate":"March 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-12T18:20:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-12 15:49:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4023457","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4023457","identity":"rs-4023457","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}