The NuroSleeve, A User-Centered 3D Printed Orthosis and Functional Electrical Stimulation System for Individuals with Upper Extremity Impairment

The NuroSleeve, A User-Centered 3D Printed Orthosis and Functional Electrical Stimulation System for Individuals with Upper Extremity Impairment | 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 The NuroSleeve, A User-Centered 3D Printed Orthosis and Functional Electrical Stimulation System for Individuals with Upper Extremity Impairment Mehdi Khantan, Mikael Avery, Phyo Thuta Aung, Rachel Marie Zarin, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2451365/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Aug, 2023 Read the published version in Journal of NeuroEngineering and Rehabilitation → Version 1 posted 10 You are reading this latest preprint version Abstract Background: Active upper extremity (UE) assistive devices have the potential to restore independent functional movement in individuals with UE impairment due to neuromuscular diseases or injury-induced chronic weakness. Academically fabricated UE assistive devices are not usually optimized for Activities of Daily Living (ADLs), whereas commercially available alternatives are prohibitively expensive. Both options are typically difficult to don and doff and are cumbersome for extensive daily use. To overcome these limitations, we have designed, developed, and clinically validated the NuroSleeve, an innovative user-centered UE orthosis. Methods: This study introduces the design, implementation, and clinical evaluation of the NuroSleeve, a user-centered, lightweight, affordable, easy to don and doff 3D-printed UE active orthosis for improving function and independence in individuals living with UE neuromuscular impairment. Our primary goals are to develop a customized active UE brace that individuals with UE impairment can use to perform ADLs and to evaluate the benefits of incorporating the device into occupational therapy sessions. The trial is designed as a prospective, open-label, single-cohort feasibility study of eight-week sessions combined with at-home use of the device and implements an iterative device design process where feedback from participants and therapists inform future design improvements. Results: All participants learned how to independently don, doff, and use the NuroSleeve in ADLs, both in clinical therapy and in their home environments. All participants showed improvements in their Canadian Occupational Performance Measure (COPM), which was the primary clinical trial outcome measure. Furthermore, the participants and therapists provided valuable feedback to guide further development. Conclusions: Our results from non-clinical testing and clinical evaluation demonstrate that the NuroSleeve has met performance and safety requirements and effectively improves independent voluntary function during ADLs. The study’s encouraging preliminary findings indicate that the NuroSleeve has met its technical and clinical objectives while improving on the limitations of the existing UE orthoses due to its personalized and flexible approach to hardware and firmware design. Trial Registration: ClinicalTrials.gov identifier: NCT04798378, https://clinicaltrials.gov/ct2/show/NCT04798378 , date of registration: March 15, 2021. assistive exoskeleton hand therapy rehabilitation stroke wearable robotics three dimensional (3D) printed active orthoses upper extremity impairment Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Neuromuscular disorders impose a significant socioeconomic burden on society. There are over 7 million stroke survivors in the United States alone [ 1 , 2 ], 62% of whom have a loss of dexterity in their upper extremities (UE) [ 3 ]. Approximately 291,000 Americans are living with disability due to spinal cord injury (SCI); [ 4 ], and Duchenne Muscular Dystrophy (DMD) and Becker Muscular Dystrophy (BMD) combined affect around 14 in 100,000 American males [ 5 ]. Neurological disorders and diseases often result in permanent disability that prevents individuals from performing Activities of Daily Living (ADLs) independently [ 4 , 6 ]. Stroke [ 1 , 7 , 8 ], SCI [ 4 , 9 , 10 ], and muscular dystrophy (MD) frequently result in debilitating UE motor impairments that persist beyond rehabilitation discharge [ 11 , 12 ]. Individuals with moderate to severe neurological UE impairment frequently exhibit limited active movement in their paretic elbow and little to no active movement in their paretic wrists and fingers [ 13 , 14 ]. Rehabilitation therapies that implement assistive neurotechnology devices tend to improve functional motor recovery, reducing impairment and improving independence in ADLs, quality of life, and community participation [ 15 – 19 ]. Over the past six decades, it has been shown that the use of active wearable neurotechnology devices benefits individuals living with UE impairment by helping them to perform ADLs [ 20 – 22 ]. Currently, commercially available active UE orthoses for home use can be divided into two groups: (1) powered mechanical orthoses [ 23 ], which use electrical motors to achieve motion; and (2) Functional Electrical Stimulation devices (FES) [ 24 , 25 ], which electrically stimulate muscles to achieve motion. Widespread use of these orthoses is hindered by several factors: (1) cost, which can range from $ 3,500 for a simple external FES up to $ 60,000 for a powered mechanical one; (2) the challenge of making them form-fitting, comfortable and lightweight; (3) the inability to customize the placement of sensors as input controls and effectors that optimize user movements; and (4) the lack of rehabilitation professionals skilled in training individuals how they can integrate the orthosis into daily routines [ 23 – 25 ]. To the best of our knowledge, no currently available commercial product offers individuals affordability, comfort, ease of use, and the ability to restore UE function during ADLs in “real world” situations [ 26 ]. Academically fabricated powered mechanical UE orthoses have their own limitations – they often need to be fixed to a wheelchair or stationary surface (e.g., a table) [ 27 – 29 ] or require support from the person’s back and shoulders [ 30 ] in order to function. Our clinical experience suggests that most individuals would not find such devices practical to use in ADLs and in the community. Soft robotic sleeves [ 31 – 37 ] provide an alternative to motor-based approaches, however, such sleeves are not easy to don and doff, and most require an air compressor or compressed gas tank to function. Hence, soft robotic sleeves may not easily find their market without first addressing their practicality and usability issues. To overcome the limitations with the currently available UE orthoses, the next generation of UE devices must be simple to use to encourage acceptance and integration in ADLs, while being affordably priced for widespread adoption. Specifically, a user-friendly orthosis would be comfortable, form-fitting, easy to don and doff, and would offer the individual a variety of options for controlling it. Furthermore, it would be lightweight; this is paramount because continuous usage of heavy UE orthoses may have a detrimental effect on user satisfaction and compliance and may contribute to physical problems such as pressure point formation, muscular fatigue, perspiration, and skin irritation [ 38 ]. These numerous requirements cannot be met in devices that are designed following the “one-size fits all” principle, without accounting for the unique needs of each individual. With this in mind, this study introduces the design, development, implementation, and clinical validation of the NuroSleeve, a novel user-centric active UE orthosis. The NuroSleeve design accommodates the unique needs and conditions of individuals by integrating (1) a user-specific control mechanism, (2) a custom 3D-printed, lightweight and easy to don and doff splint, and (3) an external FES unit. Our goal in developing the NuroSleeve is to meet the unique needs of individuals and to promote the adoption of the technology in clinical settings, at home, and in the community. Methods The NuroSleeve comprises five main components: a custom 3D-printed splint, an external FES unit, a main control unit (MCU), a clinical software suite for configuration, and a rechargeable battery, as shown in Fig. 1. The custom firmware running on the MCU receives signals from one or more input sensors, Fig. 1: The NuroSleeve consists of the main control unit (center) which accepts different input control signals (left) to control one or more end effectors (right). Implementations are customized for each patient by the occupational therapist using the clinical configuration software. processes the data in real time, and derives control signals for the effectors. The NuroSleeve firmware and hardware allow for user-specific sensor setup combined with personalized input/output mapping. In other words, sensor placement and user commands are customized for the user, as are the effector control strategies. The NuroSleeve can be controlled by one or more of the following control inputs: joystick input, electromyography (EMG) signals, inertial measurement unit (IMU) signals, and voice control. Current effector options include a mechanically operated forearm splint and an external two-channel clinical-grade FES device (see Fig. 1). It is important to emphasize that the NuroSleeve device is user-specific and is personalized with the help of an occupational therapist (OT) using the clinical configuration software. The OT can exploit rehabilitation therapy principles to help identify the optimal combination of sensor inputs and effectors, and the optimal placement of each, based on the individual’s unique abilities, needs, and functional goals. The clinical software suite permits these configurations via Bluetooth and allows for device usage monitoring, real-time data collection and visualization, and command exchange between NuroSleeve and external devices, such as brain-computer interface (BCI) systems. The NuroSleeve splint is also customized for each individual using 3D scanning and printing technologies. Each splint is built to perfectly accommodate the unique anatomy and impairment of the user to maximize comfort, efficacy, and fit. We refer to this customization process as the “Digital Orthotist” process, as it combines modern industrial design techniques with occupational therapy and orthotics know-how. The process starts with a 3D scan of the user’s impaired hand and forearm, which is then used to build a custom computer-aided designed (CAD) model of the splint. The model may be fine-tuned to suit the user as necessary and then it is 3D printed. The combination of 3D scanning and 3D printing technologies has facilitated our development of an orthosis that is lightweight, aesthetically pleasing, and form-fittingin key locations while form-adjusted in others to avoid pressure points and bony prominences [ 38 ]. The splint has an innovative clamshell design, incorporating a hinge on one side that allows the thumb and cuff sections to be opened and closed, maximizing the individual’s ability to don and doff without assistance. The use of 3D-printed rigid plastic components, rather than fabric or other soft materials, provides mechanical support and enables dynamic grasp properties, which are particularly relevant for individuals with spasticity (e.g., excessive tone) [ 39 ]. The NuroSleeve orthosis also integrates an external FES unit that can generate functional movement by stimulating paretic muscles. The application of electrical current to a person's muscles depolarizes peripheral neurons and elicits muscle contractions, allowing the person to perform a volitional movement. FES has evolved into a crucial treatment approach that clinicians may use to help individuals with stroke and SCI regains the capacity to stand, walk, reach, and grasp [ 40 ]. FES can benefit individuals by substituting or enhancing movement. Repeated muscle activation using FES may also increase voluntary motor control. This suggests that the use of FES devices improves motor recovery and can serve as a rehabilitation technique as well as assisting with ADLs [ 41 ]. The NuroSleeve is intended to be used as an assistive device, but it can be also used as a self-modulated rehabilitation device. Supplementary Table 1 lists current commercially available neuromuscular electrical stimulation devices designed for rehabilitation purposes. Device Control Method The NuroSleeve can control the linear actuator of the splint and/or the FES unit using any of the following control modes: (1) Manual control. A small joystick is fitted to the device at an accessible location for the user; (2) Voice Activation. A voice recognition module that does not require connection to the internet (this was added to the system following user feedback). This voice recognition module can extract and analyze the voice features of a speaker after a single calibration session with the individual. Following the calibration and setup session, the individual can use the voice control option to control the NuroSleeve independently and without the use of external resources; (3) EMG control. The device’s two EMG channels can be set up to control the linear actuator and/or FES with a multi-threshold approach, in which one or two signal thresholds are set up to trigger the effectors. The threshold values and their use in controlling the effectors can be customized via the clinical software suite; and/or (4) IMU control. The NuroSleeve can leverage up to two IMUs for splint and/or FES control. In IMU mode, the device can be operated in two different configurations: continuous or discrete. Continuous control configuration uses a multi-threshold approach and makes use of the IMU's 3D orientation data to continuously control the linear actuator and/or FES effectors. The discrete control configuration uses a tap-and-go control approach, in which the system uses the IMU 3D acceleration data to fully open or close the hand; each tap on the IMU sensor toggles between extraction and retraction of the linear actuator and/or FES stimulation. In other words, the IMU sensors can function as a toggle switch to control a two-state machine based on the status of the effector. The Splint Figure 2: Exploded view of NuroSleeve splint components including thumb, fingers, arm, and cuff sections. The NuroSleeve 3D printed custom splint consists of four main sections: forearm, cuff, thumb, and fingers, as shown in Fig. 2. The fingers section facilitates the opening and closing of the hand and is assisted by a splint-mounted low-profile, lightweight electro-mechanical linear actuator (PA-07, Progressive Automations, Arlington, WA) [ 42 ]. The linear actuator has a 50mm stroke length and an integrated current limiting circuit as a safeguard mechanism to avoid overtravel. The stationary part of the linear actuator is connected to the forearm section while the actuated rod is connected to the fingers section (see Fig. 2). When the linear actuator rod is extended forward, the finger piece assists the user with grasping, when the rod is retracted, it assists with hand opening. This allows the user to achieve functional flexion and extension of the metacarpophalangeal (MCP) joint of the affected hand. The forearm section of the splint has multiple endpoint modification holes for mounting the linear actuator so that its position can be adjusted. This allows for changing the start and end position of the MCP joint’s flexion and extension while keeping the range of motion (ROM) fixed. This approach allows the OT to customize the individual’s ROM endpoints, based on their clinical conditions and functional needs. Moving the linear actuator distally along the forearm, for instance, enables the user to grasp smaller objects, whereas mounting the linear actuator proximally can facilitate the grasping of larger objects. As part of the NuroSleeve calibration process, safe and optimal hand motion and grasp are carefully verified and validated by an OT to avoid any potential for injuries, such as repeated hyperflexion or hyperextension of fingers and soft tissue injuries [ 43 ]. Digital Orthotist Process To create a user-centric device that effectively matches the user's hand anatomy and functional requirements, we devised a digital splint design process that combines modern industrial design and occupational therapy techniques. This “digital orthotist” process (as shown in Fig. 3) begins with a 3D scan of the subject’s forearm and hand using the Creaform Go!SCAN 3D scanner [ 44 ], which features a volumetric accuracy [ 45 ] of 0.050 mm ± 0.150 mm/m [ 46 ] and uses proprietary software (VXmodel) [ 47 ] to create a watertight model by removing scan artifacts and superfluous information (e.g., chest-related data), overlapping or coarse surfaces, and holes. Once created, the individual watertight model is then imported into Rhinoceros [ 48 ], a 3D CAD software that features powerful design and modeling tools ideal for the creation of the custom 3D-printable UE splint. To improve the reliability and repeatability of the "digital orthotist” process, automation scripts are created within Grasshopper [ 49 ], a parametric programming tool and native plugin of Rhinoceros. While some common design elements, such as the hinge, endpoint modification holes, and joystick housing can be rescaled and modified for use in multiple models, the profile of the forearm, cuff, thumb, and fingers section of each model are unique, custom-designed by processing the user’s UE 3D scan data. Once the splint customization and creation have been completed, the 3D splint files are printed on a Markforged X7 industrial 3D printer [ 50 ] using the Onyx ™ micro carbon fiber-filled nylon [ 51 ]. Compared to other 3D printing materials, such as Nylon or Acrylonitrile Butadiene Styrene (ABS), Onyx ™ produces orthoses with superior chemical resistance, rigidity, and flexural stress [ 52 , 53 ]. All sections of the splint are printed such that the skin-contact surfaces are face up and thus not in contact with the build’s support scaffold. This ensures that the skin-contact surfaces are as smoothed as possible to reduce skin irritation. Printing a complete NuroSleeve splint requires approximately 48 hours. After printing and assembly of the splint, fabric and straps are added at specific locations to secure the user’s forearm, hand, and fingers in place. Namely, custom Oly Fun fabric wraps are attached to the finger piece and thumb piece to create a mitten-like pocket for the fingers, Oly Fun fabric was chosen because it is non-stretchy, Fig. 3: The “Digital orthotist" process begins with a 3D scan of the individual's hand and forearm. The resulting 3D mesh is then processed and imported into Rhinoceros, where with the help of custom Grasshopper scripts is converted into a personalized 3D-printable splint. Finally, the 3D-printed splint is built and assembled. allowing the fingers to stay open despite resistance, and it is non-woven, so it does not fray like other fabrics. It also breathes well, which reduces sweat and the likelihood of skin irritation. Finally, Rolyan straps and hook-and-loop tapes were used to secure the cuff and thumb sections to the forearm, preventing the clamshell hinge from opening. Rolyan straps, which are recognized for their softness and flexibility, were chosen to reduce the risk of causing skin irritation. The Functional Electrical Stimulation As depicted in Fig. 1, for FES, the NuroSleeve incorporates a two-channel commercially available neuromuscular stimulator, the Chattanooga Continuum ™ [ 54 ]. The stimulator can be controlled by any of the input control signals of the NuroSleeve. By stimulating the individual's specific muscles electrically, it is possible to generate retraction or extraction at the relevant joint. The OT can alter the intensity of stimulation based on the individual's body structure and the specific muscle being stimulated. The NuroSleeve Main Control Unit The MCU enables control of the effectors by the various control sensors. Its core component is an Arduino Nano controller module [ 55 ] with an ATMega328p [ 56 ] microcontroller, which runs the NuroSleeve firmware and allows for data collection from up to two wired Bosch BNO055 [ 57 ] intelligent 9-axis IMUs ( for motion control), up to two MyoWare 2.0 Muscle Sensors [ 58 ], (for EMG control), an ELECHOUSE Voice Recognition Module V3 [ 59 ] (for voice control) and/or a small joystick controller (for manual control) A description of the device control logic and operating principles are provided in the section below titled "Multi-threshold Control Approach". Bluetooth connectivity between the clinical software and external devices, such as BCI systems, has been implemented into the MCU via the onboard DSD TECH HC-05 [ 60 ] Bluetooth module, and the NuroSleeve proprietary Bluetooth communication protocol allows easy integration of third-party applications. The NuroSleeve device (including the linear actuator and the MCU) is powered by a single TalentCell 12V 3000mAh Lithium-ion (Li-ion) battery pack [ 61 ], consisting of three 18650 Li-ion batteries in series. To ensure adequate electrical safety, the battery pack has an integrated circuit for protection against over-charging, over-discharging, and short circuits. Clinical Software Suite The Python-based clinical software suite has been developed in-house to provide real-time management and configuration of the NuroSleeve system via Bluetooth. The software features two separate versions: a Clinical Software Suite and a User Software Suite. The Clinical Suite is designed to be used by a trained therapist and can be used to (1) customize input and output mapping; (2) adjust sensitivity and use of the input sensors; (3) visualize sensor data and settings in real-time; and (4) access and store the user compliance data from the MCU. The user suite is intended for home usage by individuals and their caregivers; it has less functionality than the Clinical Suite but permits the user to adjust the sensitivity of the sensors. User Compliance Data Monitoring The NuroSleeve is capable of logging user compliance data and storing it in a dedicated flash memory chip inside the MCU. This feature allows therapists and clinicians to monitor at-home device use between clinical appointments, and enabling Remote Therapeutic Monitoring (RTM), for which the U.S. Centers for Medicare and Medicaid Services (CMS) recently established payment policies [ 62 ]. The monitored compliance data can include the total time of device use and the amount of time spent opening and closing the hand and the time spent in each operation mode (i.e., joystick, voice, IMU, EMG), since the clinician’s last reset. These data which can help inform therapy goals and outcomes. Multi-threshold Control Approach The control strategy of the NuroSleeve can be customized to the individual's physiological needs and preferences through a quick calibration and setup phase integrated into the clinical software suite. The primary customization involves the mapping between selected input control signals (sensors) and desired outputs (effectors). Together, the individual and the treating therapist can determine which of the available inputs is most effective in controlling the effectors for that individual. If IMU inputs are selected, the sensors can be configured for continuous or toggle control. From there, the therapist and the individual can select the optimal sensor placement and activation movement for effector control. For continuous control, the effectors will be controlled by the threshold crossings of two custom-determined thresholds of the selected input signal (higher threshold and lower threshold). A positive crossing of a higher threshold triggers an effector command, while a negative crossing of a lower threshold triggers the opposite command. When the signals fall between two thresholds, the effector maintains its current state. The following equations describe how a selected sensor channel can determine the output command to a selected effector. $$Effector\: Command\left(t\right)=\left\{\begin{array}{c}OPEN,\: if(Sig\left(t\right)>HighThr) \\ CLOSE,\: if(Sig\left(t\right)<LowThr) \\ HOLD,\: if\left(LowThr\le Sig\left(t\right)\le HighThr\right),\end{array}\right.$$ where: \(Sig\left(t\right)\) is the current input signal channel (sensor) value at time t \(HighThr\) is a fixed higher threshold value configured with the software \(LowThr\) is a fixed lower threshold value configured with the software \(OPEN, CLOSE and HOLD\) are the possible output commands at time t If discrete control is selected, the NuroSleeve’s effectors are controlled with the IMU sensor acting as a toggle switch. In this configuration, the IMU signal of interest is acceleration and threshold crossing of a single threshold is used to change the state of the effector (OPEN/CLOSE for motor, ON/OFF for FES). This setup is ideal when the user desires to trigger the opening or closing of their hand by tapping the IMU sensor. $$Effector\: Command\left(t\right)=\left\{\begin{array}{c}FULLY\: OPEN,\: if(Status==CLOSED\: AND\: Sig\left(t\right)>Thr)\\ FULLY\: CLOSE,\: if\left(Status==OPEN\: AND\: Sig\left(t\right)>Thr\right) \end{array}\right.$$ It is important to emphasize that even in the discrete control mode configuration, the device control commands are updated continuously, namely, a new direction command is generated and sent to the effector at every firmware runtime update (time step = 20ms). Non-clinical Testing A battery of electrical and mechanical bench tests was conducted with the NuroSleeve to ensure that its specifications met the device requirements. The requirements evaluated included hand splint ROM, grasp force and speed, battery life, and total life cycle of the splint. While manual measurements were carried out for most requirements, accelerated life testing was also implemented using two specific setups as shown in Fig. 5. The first accelerated life test focused on the mechanical characteristics of the device, repeatedly opening and closing the hand onto a simulated test load placed below the palm to simulate object grasping. The repeated hand movements (opening/closing) were programmed to last four seconds each, while two seconds of rest were introduced between consecutive movements, resulting in a 66% linear actuator utilization (duty cycle). To fully automate the test, two force sensors and a microcontroller were integrated into the test setup to continuously monitor the device operation and collect data, including identifying the breaking point accurately. The second accelerated life test deployed a similar setup with the addition of two springs connected to the splint finger piece. The purpose of the springs was to induce a constant load of 13.3N in both extension and flexion to replicate the realistic hand movement force and effect of a spastic hand (which is opposed to extension at the MCP joint), which may decrease the splint's lifespan. Figure 5: Test Bench for the NuroSleeve with added resistance with springs To determine the battery life of the NuroSleeve, its power consumption was analyzed. In standby or FES mode, the NuroSleeve PCB with all sensors connected consumes 175mA of continuous current; movement of the linear actuator increases the current consumption to between 275mA to 375mA, depending on the torque generated. Assuming a nearly linear relationship between battery capacity and operating time due to the extremely low discharge current rate [ 63 ], the battery life of NuroSleeve is estimated to be between 8 and 17 hours. Clinical Trial In addition to the extensive non-clinical bench electrical and mechanical testing, the NuroSleeve has been evaluated in a clinical setting by various stakeholders including users, therapists, caregivers, and physicians. Continuous integration of stakeholder feedback is crucial to the development of a device with practical utility. The NuroSleeve is currently being evaluated in a clinical trial (NCT04798378), approved by the Thomas Jefferson University Institutional Review Board (IRB). Consented and enrolled participants complete an 8-week rehabilitation program that incorporates the device into occupational therapy sessions and ADLs at their homes. In brief, the trial consists of an initial (pre-intervention) clinical outcome assessment session, which establishes a baseline of each participant’s UE functional ability. The Canadian Occupational Performance Measure (COPM) [ 64 ] is also administered to identify three to five activities across multiple domains (including work, self-care, and leisure) in which the participant desires to improve their functional performance or satisfaction. Each participant then undergoes 3D scanning and receives a customized NuroSleeve, after which they engage in eight weeks of outpatient occupational therapy sessions that incorporate the device. During the sessions, the OT trains the participant on how to incorporate the NuroSleeve into their selected activities at home, so they start to use the NuroSleeve independently during daily activities. After the 8-week intervention period, the standardized outcome assessments are repeated, with and without the device being worn. Results This section details the NuroSleeve evaluation results for (1) pre-clinical bench testing and (2) clinical outcomes. Pre-clinical Bench Testing Accelerated life testing revealed that the linear actuator was the mechanical component most likely to fail. During testing in both test scenarios (with and without tension springs), the linear actuator failed before any of the 3D-printed components failed or exhibited any signs of wear and mechanical fatigue. The linear actuator failed after 86 hours of continuous operation (totaling 26361 actuations) in the first accelerated life test that simulated grasping an object and after only 47 hours (totaling 14269 actuation) in the second test under constant load, with the additional 13.3 N spring force. As expected, the test with the springs caused the linear actuator to fail in almost half of the time, due to the increased torque requirements. In both tests, the linear actuator stopped working due to the failure of the internal gearbox, which resulted in a higher than nominal current draw of the direct current (DC) motor and eventually triggered the linear actuator’s onboard safety power cut-off circuitry. Despite the linear actuator failure preventing the NuroSleeve from being functional, such a failure mode poses no risk to the user and can therefore be categorized as a safe failure. In both accelerated life tests, the linear actuator duty cycle (ratio between the actuation and stationary time durations) was 66% (4 seconds on, 2 seconds off), which is much greater than the 10%-20% nominal duty cycle specified for the PA-07 linear actuator [65]. Utilizing this linear actuator with high-duty cycles leads to excessive operational temperatures and mechanical wear, which can eventually lead to premature failure. Based on these initial findings, additional testing will be performed to better characterize the device's expected life span and maintenance intervals. The NuroSleeve’s battery life was tested with continuous extension and flexion movement lasting for 4 seconds with a 2-second rest in between. An important requirement for an effective UE orthosis that may be effectively incorporated into ADLs is to operate for more than 8 hours on a single battery charge. With no external loading, the battery life was 13 hours; with a constant load of 13.3 N, the battery life was 11 hours. These results are better than the anticipated (calculated) battery life because the linear actuator in these tests was not operating at maximum torque. Initial clinical trial findings indicate that the NuroSleeve’s battery in real-life usage is substantially longer, with participants only needing to recharge the battery once a week. This discrepancy is likely because the linear actuator’s “real-life” duty cycle is much lower than those tested on the bench, and depends upon the wearer’s flexion and extension rate, body size, and level of spasticity/tone in their hand. Depending on the individual's hand size, the splint weighs between 175g and 310g, the control unit weighs 310g, and the FES system weighs 200g. The NuroSleeve has been designed to address the limitations of currently available commercial orthoses. Table 1 compares some characteristics of commercially available UE mobility-assistive devices to those of the NuroSleeve, showing how the latter overcomes most of the common limitations. The NuroSleeve has been designed to be affordable and priced under $ 5,000. For reference, Table 2 introduces an itemized list and cost of the components, which total about $ 900 (not including labor or the cost of the machine shop facility and equipment). The performance testing results demonstrate that the device has met the desired technical and functional requirements. The above-mentioned properties combined with a lightweight (less than 310g) and custom-fitting splint ensure that the NuroSleeve device can be easily used by people with UE impairment during ADLs and can help them become more independent in both the home and community settings. Clinical Trial Outcomes Figure 6: Performance and satisfaction scores on the COPM for NS1, NS3, NS4, NS6, NS7 (Per. = Performance, Sat. = Satisfaction). COPM was performed three times, once at the beginning of the trial and twice at the end of the trial with and without the device. The bars represent COPM scores. The black bars are for the pre-trial scores (baseline), the pink bars are for the post-trial scores without the device, while the blue bars are for the post-trial scores with the device. At the time of this report, five individuals with hemiparesis from chronic stroke have completed participation in the NuroSleeve clinical trial. The trial intervention comprises three one-hour occupational therapy sessions per week and daily home use of the NuroSleeve, for a total of 8 weeks. The primary clinical outcome measure is the COPM [ 64 ], for which we report results in Fig. 6. Secondary outcome measures include the Action Research Arm Test (ARAT) [ 66 – 68 ], Box and Blocks Test (BBT) [ 19 , 67 ], ABILHAND [ 69 ], and the Patient-Reported Outcomes Measurement Information System UE Short Form Version 2.0 (PROMIS UE SF V2.0) [ 70 , 71 ]; however, results of these will be reported in a separate paper. All outcome measures are administered both before and after the eight-week intervention. In the post-intervention evaluation, each measure is administered with and without the NuroSleeve. The COPM is a self-reported measure, so for each self-selected task, the participant rates their ability to perform it and satisfaction with performing it. They rate it on an ordinal scale ranging from “1" (cannot do/not satisfied) to "10" (can perform well/very satisfied), both before and after the trial intervention. A two-point increase in score indicates a clinically meaningful improvement. Results from the first five trial participants (NS1, NS3, NS4, NS6, and NS7) are reported in Fig. 6. All five participants were successfully fitted with a customized NuroSleeve and participated in all 24 occupational therapy sessions over 8 weeks. All participants learned how to don and doff the NuroSleeve on their own and were able to use the device at home. Most importantly, all but one participant improved on the primary outcome measure and provided valuable feedback to guide future design improvements. Although myoelectric control was available, all participants and their OTs found the joystick and IMUs to be a more reliable and practical control mode. All participants used IMU-controlled NuroSleeve in their homes without requiring additional calibration or adjustments, providing evidence that this control method is reliable and practical [ 23 , 25 , 72 ]. Based on the trial participants’ feedback and our experience with other devices, the IMU control method appears to be more reliable, more consistent, and easier to use than the EMG one. The clinical findings shown in Fig. 6 demonstrate that all participants reported improvement in the performance of, and satisfaction with, most of their self-identified goals when the device was in use. For many participants, the improvement was clinically meaningful; in three of four goals chosen by NS1, one of three identified by NS3, six of eight identified by NS4, and three of five identified by NS7, improvement exceeded the two-point threshold for a clinically meaningful change. NS6 did not have any clinically meaningful change. Both NS1 and NS7 reported performance and satisfaction scores of 9 while using the device – close to the maximum score of ten. Discussion The integration of 3D scanning and 3D printing technologies into orthosis manufacturing has paved the way for the creation of custom, form-fitting orthoses that meet the user's anatomical and functional needs. Studies indicate that the comfort and effectiveness of 3D-printed orthoses surpass those of conventional orthoses [ 73 ]. In addition to being more comfortable and effective, 3D-printed orthoses are lighter in weight and more affordable; all of these advantages are at the core of NuroSleeve’s design approach [ 31 , 32 , 73 , 74 ]. The current NuroSleeve is the result of several iterations based on the feedback received from study participants and OTs as part of the ongoing clinical trial. The primary design changes implemented thus far include: (1) the 3D model was altered by removing material at the wrist to avoid contact with bony prominences; (2) the thumb and cuff pieces were separated into two distinct pieces, allowing the user to more easily don and doff the splint; (3) the joystick controller has been mounted onto the splint making it more convenient for the user to control the device with their unimpaired hand. We found this to be extremely helpful for individuals who rely on their unaffected hand to support and move their impaired arm; since the unimpaired hand typically provides support in the proximity of the contralateral forearm, placing the joystick in this area allows for quick and easy access to it. Although, the NuroSleeve can be controlled by EMG signals, which are highly correlated with voluntary UE movements, based on previous studies [ 75 – 77 ], our experience, and participant feedback, EMG signals tend to be erratic, so this is the least preferred control method. Although the clinical results presented are from a small cohort of participants in a feasibility study, it should be noted that there is no plausible physiologic or physical process by which random chance would account for the functional improvements seen in these participants: all of them had been living with chronic deficits for two or more years following a stroke and had already exhausted standard rehabilitation therapy. Most importantly, each served as their own control and compared function with and without the device, demonstrating that the benefits were due to the device, not a non-specific mass practice effect. The functional improvements observed merit a prospective, randomized, controlled trial, with an adequate sample size to be able to differentiate the relative contributions of traditional rehabilitation therapy alone, traditional rehabilitation with the NuroSleeve, and abbreviated rehabilitation with the NuroSleeve. In addition to the promising preliminary findings, this trial demonstrates a successful model for the future of UE rehabilitation methods, an interdisciplinary approach where a team comprised of neurology, engineering, software development, industrial design, and occupational therapy professionals collaborate to design and create a customizable, durable, affordable, and genuinely functional assistive device. Conclusions Loss of independence due to UE neuromuscular impairment represents a high socio-economic burden for society. Current rehabilitation methods and commercially available UE active orthoses seem to be limited in their ability to restore function and thus improve independence in individuals living with UE impairment. The NuroSleeve has been designed, developed, and clinically validated to address these limitations. The NuroSleeve is an innovative user-centric 3D-printed UE active orthosis and closed-loop FES system that improves function and independence in ADLs of individuals living with UE neuromuscular impairment. To overcome the limitations of existing neurotechnology, the NuroSleeve deploys 3D printing and introduces a design that is user-centered, lightweight, affordable, easy to don and doff, and user-friendly. Furthermore, the NuroSleeve implements innovative options for control methods (inputs) and effectors (outputs) that can be customized and used in various combinations and result in a functionally and clinically effective active orthosis for both home and clinical use. Current control methods include manual, EMG, IMU, and voice controls, while the effectors include a linear actuator that opens and closes the hand and two channels of FES. The team will continue its research and development activities to improve upon the device design and functionality; for example, work is underway to incorporate an elbow brace into the NuroSleeve, which would provide the user more degrees of freedom (DOF), particularly arm flexion and extension. We also aim to make the control sensors wireless and to improve the battery life so the user may operate it for longer time without needing to recharge. The NuroSleeve was pre-clinically evaluated using state-of-the-art bench testing to ensure adequate performance, safety, and quality of metrics. Bench test results demonstrate that the NuroSleeve meets all of its technical objectives and operational requirements, due to its customizable and flexible hardware and firmware designs. Preliminary findings of the clinical trial reveal that NuroSleeve meets its clinical objectives and addresses previously unmet clinical needs. The NuroSleeve has shown benefit to the individuals who have enrolled in the ongoing trial; however, it can only become beneficial and available to the large population of individuals living with UE impairment if it becomes a commercially available FDA-cleared medical device. To achieve this goal, a product development plan is in place, which includes: an FDA-compliant Quality Management System, a redesign and optimization, further bench testing to meet all FDA requirements, and a subsequent pivotal clinical trial. Such steps will ensure that future iterations of the NuroSleeve may be available to more individuals with UE impairment and potentially become part of clinical care. Abbreviations 3D three dimensional UE upper extremities SCI spinal cord injury DMD Duchenne Muscular Dystrophy BMD Becker Muscular Dystrophy ADLs Activities of Daily Living MD muscular dystrophy FES Functional Electrical Stimulation MCU main control unit EMG electromyography IMU inertial measurement unit OT occupational therapist BCI brain computer interface CAD computer-aided design MCP metacarpophalangeal ROM range of motion ABS Acrylonitrile Butadiene Styrene FDA Food and Drug Administration EMI electromagnetic interference PCB printed circuit board Li-ion Lithium-ion RTM Remote Therapeutic Monitoring CMS Medicare and Medicaid Services IRB Institutional Review Board COPM Canadian Occupational Performance Measure DC direct current ARAT Action Research Arm Test BBT Box and Blocks Test PROMIS UE SF V2.0 Patient-Reported Outcomes Measurement Information System UE Short Form Version 2.0 DOF degrees of freedom Declarations Ethics approval and consent to participate This study has been approved by the Institutional Review Board at Thomas Jefferson University. All participants provided written informed consent before participating. Consent for publication Not applicable Availability of data and materials All data generated or analyzed during this study are included in this published article. Competing interests M.D.S., A.N., and M.A. are inventors on a US provisional patent application that has been filed by Thomas Jefferson University on the methods described in this paper. All other authors report that they do not have any conflicts of interest with the research described. Funding This research was supported by philanthropy to the Farber Institute of Neuroscience at Thomas Jefferson University. Authors' Contributions A.N. leads and oversees the design and production of NuroSleeve, while M.D.S. designed and oversees the clinical trial. M.A. designed the splint pieces and optimized the 3D model. M.K. designed the circuitry, P.A. wrote the device software and firmware, and R.M.Z. designed the MCU housing and oversaw 3D printing and device assembly. R.M.Z. and M.K. designed the bench tests and tabulated results, and E.H. provided the clinical outcomes. N.S. assisted with the literature review, reference management and review of the manuscript. A.N. and M.K. directed the preparation of the manuscript, to which all authors contributed. All authors read and approved the final manuscript. Acknowledgments The authors wish to thank the members of the Center for Neurorestoration for their assistance with and dedication to this endeavor, particularly Erica Jones for support with trial logistics, Joe Kardine for developing the occupational therapy protocol optimally suited for the NuroSleeve, and Saami Zakaria for helping to integrate the voice recognition module into the device. They acknowledge the contributions of Drs. Mary Jane “MJ” Mulcahey and Namrata Grampurohit towards trial design, and Dr. Robert H. Rosenwasser for continual support at the institutional level. The authors want to recognize Dr. Iyad Obeid and Michelle A. Keon for general advice and content editing respectively. Finally, the authors greatly appreciate each participant’s time and engagement in the study, especially during the pandemic. References O’Neill C, Proietti T, Nuckols K, Clarke ME, Hohimer CJ, Cloutier A, et al. Inflatable Soft Wearable Robot for Reducing Therapist Fatigue During Upper Extremity Rehabilitation in Severe Stroke. IEEE Robot Autom Lett. 2020;5:3899–906. Stroke Facts & Statistics. Stroke Awareness Foundation. 2021. https://www.strokeinfo.org/stroke-facts-statistics/ . Accessed 17 Dec 2022. Allison R, Shenton L, Bamforth K, Kilbride C, Richards D, Incidence. Time Course and Predictors of Impairments Relating to Caring for the Profoundly Affected arm After Stroke: A Systematic Review. Physiother Res Int. 2016;21:210–27. Dunkelberger N, Schearer EM, O’Malley MK. A review of methods for achieving upper limb movement following spinal cord injury through hybrid muscle stimulation and robotic assistance. Exp Neurol. 2020;328:113274. What is Muscular Dystrophy? Centers for Disease Control and Prevention. 2020. https://www.cdc.gov/ncbddd/musculardystrophy/facts.html . Accessed 4 Nov 2022. Garcia-Garcia LA, Rodríguez M. Competitive and technology intelligence to reveal the most influential authors and inter-institutional collaborations on additive manufacturing for hand orthoses. J Intell Stud Bus. 2019;8:32–44. Norouzi-Gheidari N, Hernandez A, Archambault PS, Higgins J, Poissant L, Kairy D, Feasibility. Safety and Efficacy of a Virtual Reality Exergame System to Supplement Upper Extremity Rehabilitation Post-Stroke: A Pilot Randomized Clinical Trial and Proof of Principle.Int J Environ Res Public Health. 2019;17. Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, et al. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation. 2021;143:e254–743. de Miguel-Rubio A, Rubio MD, Alba-Rueda A, Salazar A, Moral-Munoz JA, Lucena-Anton D. Virtual Reality Systems for Upper Limb Motor Function Recovery in Patients With Spinal Cord Injury: Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth. 2020;8:e22537. Yozbatiran N, Francisco GE. Robot-assisted Therapy for the Upper Limb after Cervical Spinal Cord Injury. Phys Med Rehabil Clin N Am. 2019;30:367–84. Janssen MMHP, Harlaar J, Koopman B, de Groot IJM. Unraveling upper extremity performance in Duchenne muscular dystrophy: A biophysical model. Neuromuscul Disord. 2019;29:368–75. Crisafulli S, Sultana J, Fontana A, Salvo F, Messina S, Trifirò G. Global epidemiology of Duchenne muscular dystrophy: an updated systematic review and meta-analysis. Orphanet J Rare Dis. 2020;15:141. Block VAJ, Pitsch E, Tahir P, Cree BAC, Allen DD, Gelfand JM. Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review. PLoS One. 2016;11:e0154335. Singh H, Unger J, Zariffa J, Pakosh M, Jaglal S, Craven BC, et al. Robot-assisted upper extremity rehabilitation for cervical spinal cord injuries: a systematic scoping review. Disabil Rehabil Assist Technol. 2018;13:704–15. Lang CE, Bland MD, Bailey RR, Schaefer SY, Birkenmeier RL. Assessment of upper extremity impairment, function, and activity after stroke: foundations for clinical decision making. J Hand Ther. 2013;26:104–15. Lo AC, Guarino PD, Richards LG, Haselkorn JK, Wittenberg GF, Federman DG, et al. Robot-assisted therapy for long-term upper-limb impairment after stroke. N Engl J Med. 2010;362:1772–83. Wolf SL, Winstein CJ, Miller JP, Taub E, Uswatte G, Morris D, et al. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA. 2006;296:2095–104. Page SJ, Levine P, Leonard A. Mental practice in chronic stroke: results of a randomized, placebo-controlled trial. Stroke. 2007;38:1293–7. Kontson K, Marcus I, Myklebust B, Civillico E. Targeted box and blocks test: Normative data and comparison to standard tests. PLoS ONE. 2017;12:e0177965. Maceira-Elvira P, Popa T, Schmid A-C, Hummel FC. Wearable technology in stroke rehabilitation: towards improved diagnosis and treatment of upper-limb motor impairment. J Neuroeng Rehabil. 2019;16:142. Xiloyannis M, Chiaradia D, Frisoli A, Masia L. Physiological and kinematic effects of a soft exosuit on arm movements. J Neuroeng Rehabil. 2019;16:29. Iwamoto Y, Imura T, Suzukawa T, Fukuyama H, Ishii T, Taki S, et al. Combination of Exoskeletal Upper Limb Robot and Occupational Therapy Improve Activities of Daily Living Function in Acute Stroke Patients. J Stroke Cerebrovasc Dis. 2019;28:2018–25. Myomo, Myomo. https://myomo.com/. Accessed 22 Nov 2022. H200 wireless - Bioness. Bioventus. 2021. https://bionessrehab.com/h200/ . Accessed 6 Nov 2022. Omnihi5™. Accelerated Care Plus Corporation (ACP). https://acplus.com/omnihi5 . Accessed 6 Nov 2022. Bos RA, Haarman CJW, Stortelder T, Nizamis K, Herder JL, Stienen AHA, et al. A structured overview of trends and technologies used in dynamic hand orthoses. J Neuroeng Rehabil. 2016;13:62. Rahman T, Sample W, Seliktar R, Alexander M, Scavina M. A body-powered functional upper limb orthosis. J Rehabil Res Dev. 2000;37:675–80. Holley D, Johnson M, Harris G, Beardsley S. A modular low-clearance wrist orthosis for improving wrist motion in children with cerebral palsy. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2014;2014:3069–72. Morinière B, Verney A, Abroug N, Garrec P, Perrot Y. EMY: a dual arm exoskeleton dedicated to the evaluation of Brain Machine Interface in clinical trials. 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2015. p. 5333–8. Kooren PN, Dunning AG, Janssen MMHP, Lobo-Prat J, Koopman BFJM, Paalman MI, et al. Design and pilot validation of A-gear: a novel wearable dynamic arm support. J Neuroeng Rehabil. 2015;12:83. Koiliaris P. 3D Printed Soft Fluidic Actuator for an Assistive Hand Exoskeleton Device [Master Thesis]. [Mekelweg, Netherlands]: Delft University of Technology; 2018. Zhao H, Jalving J, Huang R, Knepper R, Ruina A, Shepherd R. A Helping Hand: Soft Orthosis with Integrated Optical Strain Sensors and EMG Control. IEEE Robot Autom Mag. 2016;23:55–64. Cho KH, Kim Y, Yang SY, Kim K, Park JH, Rodrigue H, et al. Artificial musculoskeletal actuation module driven by twisted and coiled soft actuators. Smart Mater Struct IOP Publishing. 2019;28:125010. Chen Y, Tan X, Yan D, Zhang Z, Gong Y. A Composite Fabric-Based Soft Rehabilitation Glove With Soft Joint for Dementia in Parkinson’s Disease. IEEE J Transl Eng Health Med. 2020;8:1400110. Bae J-H, Kim Y-M, Moon I. Wearable hand rehabilitation robot capable of hand function assistance in stroke survivors. 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob). Rome, Italy: IEEE; 2012. p. 1482–7. Patar MNAA, Komeda T, Low CY, Mahmud J. System Integration and Control of Finger Orthosis for Post Stroke Rehabilitation. Procedia Technol. 2014;15:755–64. Meng W, Sheng B, Klinger M, Liu Q, Zhou Z, Xie SQ. Design and control of a robotic wrist orthosis for joint rehabilitation. 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). Busan, Korea (South): IEEE; 2015. p. 1235–40. McKee P, Nguyen C. Customized dynamic splinting: orthoses that promote optimal function and recovery after radial nerve injury: a case report. J Hand Ther. 2007;20:73–87. quiz 88. Xu Y, Li X, Chang Y, Wang Y, Che L, Shi G, et al. Design of Personalized Cervical Fixation Orthosis Based on 3D Printing Technology. Appl Bionics Biomech. 2022;2022:8243128. Marquez-Chin C, Popovic MR. Functional electrical stimulation therapy for restoration of motor function after spinal cord injury and stroke: a review. Biomed Eng Online. 2020;19:34. Quandt F, Hummel FC. The influence of functional electrical stimulation on hand motor recovery in stroke patients: a review. Exp Transl Stroke Med. 2014;6:9. Micro Linear Actuator. Progressive Automations. https://www.progressiveautomations.com/products/micro-linear-actuator?variant=18277344575555 . Accessed 22 Nov 2022. Giese J, Cerniglia C. Soft Tissue Injuries of the Finger and Thumb. Seminars in Ultrasound. CT and MRI. 2018;39:397–410. Go!SCAN 3D. (White Light Portable [3D Object Scanner]). Creaform. https://www.creaform3d.com/en/handheld-portable-3d-scanner-goscan-3d . Accessed 22 Nov 2022. Chromy A. High-Accuracy Volumetric Measurements of Soft Tissues using Robotic 3D Scanner. IFAC-PapersOnLine. 2015;48:318–23. Go!SCAN 3D scanner [technical specifications]. Creaform. https://www.creaform3d.com/en/handheld-portable-3d-scanner-goscan-3d/technical-specifications . Accessed 22 Nov 2022. VXmodel. : scan-to-CAD software module. Creaform. https://www.creaform3d.com/en/metrology-solutions/3d-applications-software-platforms/vxmodel-scan-cad-software-module . Accessed 22 Nov 2022. McNeel R. Rhinoceros 3D. www.rhino3d.com. Accessed 22 Nov 2022. Davidson S, Grasshopper. https://www.grasshopper3d.com/ . Accessed 22 Nov 2022. X7 Industrial Carbon Fiber 3D Printer. Markforged. https://markforged.com/3d-printers/x7 . Accessed 22 Nov 2022. Onyx - Composite 3D Printing Material. Markforged. https://markforged.com/materials/plastics/onyx . Accessed 22 Nov 2022. MATERIAL DATASHEET Composites - Markforged. Markforged. https://static.markforged.com/downloads/composites-data-sheet.pdf . Accessed 22 Nov 2022. Bárnik F, Vaško M, Sága M, Handrik M, Sapietová A. Mechanical properties of structures produced by 3D printing from composite materials. MATEC Web of Conferences. 2019;254:01018. Chattanooga®, Continuum. ™ . Chattanooga®. https://www.chattanoogarehab.com/us/chattanooga-continuumtm-2600-dev . Accessed 11 Dec 2022. Nano | Arduino Documentation. Arduino. https://docs.arduino.cc/hardware/nano . Accessed 11 Dec 2022. ATmega328P. Microchip Technology. https://www.microchip.com/en-us/product/ATmega328P . Accessed 27 Nov 2022. Smart sensor BNO055. Bosch Sensortec. https://www.bosch-sensortec.com/products/smart-sensors/bno055/ . Accessed 27 Nov 2022. MYOWARE 2.0 TECH SPECS: Muscle Sensor. MYOWARE by Advancer Technologies. 2022. https://myoware.com/products/technical-specifications/#muscle-sensor . Accessed 27 Nov 2022. Speak recognition, voice recognition module V3. ELECHOUSE. 2022. https://www.elechouse.com/product/speak-recognition-voice-recognition-module-v3/ . Accessed 27 Nov 2022. DSD Tech HC. -05 bluetooth serial pass-through module wireless serial communication with button for Arduino. http://www.dsdtech-global.com/2017/07/dsd-tech-hc-05-bluetooth-serial-pass.html . Accessed 27 Nov 2022. YB1203000–12V Lithium ion battery. Talentcell Technology Co.,Ltd. https://talentcell.com/lithium-ion-battery/12v/yb1203000.html . Accessed 27 Nov 2022. Home - Centers for Medicare &. Medicaid Services. CMS. https://www.cms.gov/ . Accessed 7 Dec 2022. Lain MJ, Kendrick E. Understanding the limitations of lithium ion batteries at high rates. J Power Sources. 2021;493:229690. Donnelly C, O’Neill C, Bauer M, Letts L. Canadian Occupational Performance Measure (COPM) in Primary Care: A Profile of Practice. Am J Occup Ther. 2017;71:7106265010p1–8. Micro Linear Actuator. Progressive Automations. https://www.progressiveautomations.com/products/micro-linear-actuator?variant=18277344575555 . Accessed 27 Nov 2022. Yozbatiran N, Der-Yeghiaian L, Cramer SC. A standardized approach to performing the action research arm test. Neurorehabil Neural Repair. 2008;22:78–90. Mathiowetz V, Volland G, Kashman N, Weber K. Adult norms for the Box and Block Test of manual dexterity. Am J Occup therapy. 1985;39:386–91. Lyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res. 1981;4:483–92. Penta M, Thonnard JL, Tesio L. ABILHAND: a Rasch-built measure of manual ability. Arch Phys Med Rehabil. 1998;79:1038–42. Resnik LJ, Stevens PM, Ni P, Borgia ML, Clark MA. Assessment of Patient-Reported Physical Function in Persons with Upper Extremity Amputation: Comparison of Short Form instruments drawn from the PROMIS v2.0 Upper Extremity item bank. Am J Phys Med Rehabil. 2022. 10.1097/PHM.0000000000002044 . PROMIS: Patient-reported Outcomes Measurement Information System - home page. National Institutes of Health, U.S. Department of Health and Human Services. 2019. https://commonfund.nih.gov/promis/index . Accessed 30 Dec 2022. L300 go. Bioness. 2022. https://bionessrehab.com/l300 . Accessed 27 Nov 2022. Choo YJ, Boudier-Revéret M, Chang MC. 3D printing technology applied to orthosis manufacturing: narrative review. Ann Palliat Med. 2020;9:4262–70. Lu P, Liao Z, Zeng Q, Chen H, Huang W, Liu Z, et al. Customized Three-Dimensional-Printed Orthopedic Close Contact Casts for the Treatment of Stable Ankle Fractures: Finite Element Analysis and a Pilot Study. ACS Omega. 2021;6:3418–26. Resnik LJ, Acluche F, Lieberman Klinger S. User experience of controlling the DEKA Arm with EMG pattern recognition. PLoS ONE. 2018;13:e0203987. Xie T, Leng Y, Zhi Y, Jiang C, Tian N, Luo Z et al. Increased Muscle Activity Accompanying With Decreased Complexity as Spasticity Appears: High-Density EMG-Based Case Studies on Stroke Patients.Front Bioeng Biotechnol. 2020;8. Lueken MJ, Misgeld BJE, Leonhardt S. Classification of spasticity affected EMG-signals. 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN). Cambridge, MA, USA: IEEE; 2015. p. 1–6. Tables Tables 1 and 2 are available in the Supplementary Files section. Additional Declarations Competing interest reported. M.D.S., A.N., and M.A. are inventors on a US provisional patent application that has been filed by Thomas Jefferson University on the methods described in this paper. All other authors report that they do not have any conflicts of interest with the research described. Supplementary Files Table1.xls Table2.xls Supplementary.docx Cite Share Download PDF Status: Published Journal Publication published 04 Aug, 2023 Read the published version in Journal of NeuroEngineering and Rehabilitation → Version 1 posted Editorial decision: Major revision 14 Apr, 2023 Reviews received at journal 27 Feb, 2023 Reviewers agreed at journal 13 Feb, 2023 Reviewers agreed at journal 30 Jan, 2023 Reviews received at journal 30 Jan, 2023 Reviewers agreed at journal 30 Jan, 2023 Reviewers invited by journal 29 Jan, 2023 Editor assigned by journal 09 Jan, 2023 Submission checks completed at journal 09 Jan, 2023 First submitted to journal 06 Jan, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-2451365","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":166070719,"identity":"f29c43be-e011-41ed-a10a-f04154f04679","order_by":0,"name":"Mehdi Khantan","email":"","orcid":"","institution":"Temple University","correspondingAuthor":false,"prefix":"","firstName":"Mehdi","middleName":"","lastName":"Khantan","suffix":""},{"id":166070720,"identity":"028a6ed4-c8a4-4727-bc35-31091d3f3145","order_by":1,"name":"Mikael Avery","email":"","orcid":"","institution":"Studio Krea","correspondingAuthor":false,"prefix":"","firstName":"Mikael","middleName":"","lastName":"Avery","suffix":""},{"id":166070721,"identity":"a037d36f-d2f4-4682-887b-f96e1a9ecef6","order_by":2,"name":"Phyo Thuta Aung","email":"","orcid":"","institution":"Thomas Jefferson University","correspondingAuthor":false,"prefix":"","firstName":"Phyo","middleName":"Thuta","lastName":"Aung","suffix":""},{"id":166070722,"identity":"7eb27b4f-1059-4fd9-969c-8682d83c675e","order_by":3,"name":"Rachel Marie Zarin","email":"","orcid":"","institution":"Thomas Jefferson University","correspondingAuthor":false,"prefix":"","firstName":"Rachel","middleName":"Marie","lastName":"Zarin","suffix":""},{"id":166070723,"identity":"9a1710c7-44aa-487f-8161-d4e016b21f74","order_by":4,"name":"Emma Hammelef","email":"","orcid":"","institution":"Thomas Jefferson University","correspondingAuthor":false,"prefix":"","firstName":"Emma","middleName":"","lastName":"Hammelef","suffix":""},{"id":166070724,"identity":"5f4c84a0-10cf-47bd-b788-d11218749d27","order_by":5,"name":"Nabila Shawki","email":"","orcid":"","institution":"Thomas Jefferson University","correspondingAuthor":false,"prefix":"","firstName":"Nabila","middleName":"","lastName":"Shawki","suffix":""},{"id":166070725,"identity":"f28ee4d4-3d18-4762-a279-85be1275196f","order_by":6,"name":"Mijail Demian Serruya","email":"","orcid":"","institution":"Thomas Jefferson University","correspondingAuthor":false,"prefix":"","firstName":"Mijail","middleName":"Demian","lastName":"Serruya","suffix":""},{"id":166070726,"identity":"07d041e8-404b-4c2c-a48b-c5c750f65e65","order_by":7,"name":"Alessandro Napoli","email":"data:image/png;base64,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","orcid":"","institution":"Thomas Jefferson University","correspondingAuthor":true,"prefix":"","firstName":"Alessandro","middleName":"","lastName":"Napoli","suffix":""}],"badges":[],"createdAt":"2023-01-06 17:59:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2451365/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2451365/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12984-023-01228-2","type":"published","date":"2023-08-04T21:51:23+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":31432480,"identity":"b31fb0b5-f0e2-46d9-aa7c-6e0ce53289be","added_by":"auto","created_at":"2023-01-11 15:44:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":803944,"visible":true,"origin":"","legend":"\u003cp\u003eThe NuroSleeve consists of the main control unit (center) which accepts different input control signals (left) to control one or more end effectors (right). Implementations are customized for each patient by the occupational therapist using the clinical configuration software.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/1647e3e56217bf0b8e1640d3.png"},{"id":31431050,"identity":"fce39563-37ac-400b-8928-8b77c5b0ccb9","added_by":"auto","created_at":"2023-01-11 15:36:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":738835,"visible":true,"origin":"","legend":"\u003cp\u003eExploded view of NuroSleeve splint components including thumb, fingers, arm, and cuff sections.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/f0a3ac384e3acbda3bbf21ba.png"},{"id":31432482,"identity":"5ebfa724-2455-4a3f-b84d-7dc406631e09","added_by":"auto","created_at":"2023-01-11 15:44:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1957104,"visible":true,"origin":"","legend":"\u003cp\u003eThe “Digital orthotist\" process begins with a 3D scan of the individual's hand and forearm. The resulting 3D mesh is then processed and imported into Rhinoceros, where with the help of custom Grasshopper scripts is converted into a personalized 3D-printable splint. Finally, the 3D-printed splint is built and assembled.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/aa875d929dc85df842306e34.png"},{"id":31432481,"identity":"74220b30-556d-450d-a961-71e798e6b782","added_by":"auto","created_at":"2023-01-11 15:44:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4105489,"visible":true,"origin":"","legend":"\u003cp\u003eMain Control Unit (MCU) of the NuroSleeve with the 3D printed housing. Each MCU is assembled and tested in house before being deployed in the clinical trial\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/b9b9f19b8f3158fe7eeff48c.png"},{"id":31431056,"identity":"03f94e98-a5df-4c46-ac6c-667b17b96721","added_by":"auto","created_at":"2023-01-11 15:36:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4122009,"visible":true,"origin":"","legend":"\u003cp\u003eTest Bench for the NuroSleeve with added resistance with springs\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/9792b0c49330eb36f2caa7ac.png"},{"id":31431054,"identity":"8a094c1c-b76f-47d7-80f9-5a532cc9e9bc","added_by":"auto","created_at":"2023-01-11 15:36:08","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":808968,"visible":true,"origin":"","legend":"\u003cp\u003ePerformance and satisfaction scores on the COPM for NS1, NS3, NS4, NS6, NS7 (Per. = Performance, Sat. = Satisfaction). COPM was performed three times, once at the beginning of the trial and twice at the end of the trial with and without the device. The bars represent COPM scores. The black bars are for the pre-trial scores (baseline), the pink bars are for the post-trial scores without the device, while the blue bars are for the post-trial scores with the device.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/5acf17ad20971391534d06ae.png"},{"id":44736214,"identity":"167722ca-c7cc-400b-bd9c-cfea0c72764b","added_by":"auto","created_at":"2023-10-16 22:29:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5782950,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/9e230eb6-f0fe-4a35-9506-02b25620189f.pdf"},{"id":31432479,"identity":"4320b08b-d8ac-46b9-a95f-476abfd20eb1","added_by":"auto","created_at":"2023-01-11 15:44:08","extension":"xls","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18944,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.xls","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/a893beab8c368fdc062755cd.xls"},{"id":31431048,"identity":"269f68de-7f87-4fb4-9761-bc48b6cb4891","added_by":"auto","created_at":"2023-01-11 15:36:08","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18432,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.xls","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/b35d7c8b918412ad6c508a06.xls"},{"id":31431052,"identity":"e42163d0-e6c9-47e9-9627-061cdc76a2bf","added_by":"auto","created_at":"2023-01-11 15:36:08","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":26480,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-2451365/v1/fac0119976406e9ce9eb70f2.docx"}],"financialInterests":"Competing interest reported. M.D.S., A.N., and M.A. are inventors on a US provisional patent application that has been filed by Thomas Jefferson University on the methods described in this paper. All other authors report that they do not have any conflicts of interest with the research described.","formattedTitle":"The NuroSleeve, A User-Centered 3D Printed Orthosis and Functional Electrical Stimulation System for Individuals with Upper Extremity Impairment","fulltext":[{"header":"Background","content":"\u003cp\u003eNeuromuscular disorders impose a significant socioeconomic burden on society. There are over 7\u0026nbsp;million stroke survivors in the United States alone [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], 62% of whom have a loss of dexterity in their upper extremities (UE) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Approximately 291,000 Americans are living with disability due to spinal cord injury (SCI); [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and Duchenne Muscular Dystrophy (DMD) and Becker Muscular Dystrophy (BMD) combined affect around 14 in 100,000 American males [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Neurological disorders and diseases often result in permanent disability that prevents individuals from performing Activities of Daily Living (ADLs) independently [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Stroke [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], SCI [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and muscular dystrophy (MD) frequently result in debilitating UE motor impairments that persist beyond rehabilitation discharge [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Individuals with moderate to severe neurological UE impairment frequently exhibit limited active movement in their paretic elbow and little to no active movement in their paretic wrists and fingers [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRehabilitation therapies that implement assistive neurotechnology devices tend to improve functional motor recovery, reducing impairment and improving independence in ADLs, quality of life, and community participation [\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Over the past six decades, it has been shown that the use of active wearable neurotechnology devices benefits individuals living with UE impairment by helping them to perform ADLs [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCurrently, commercially available active UE orthoses for home use can be divided into two groups: (1) powered mechanical orthoses [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], which use electrical motors to achieve motion; and (2) Functional Electrical Stimulation devices (FES) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], which electrically stimulate muscles to achieve motion. Widespread use of these orthoses is hindered by several factors: (1) cost, which can range from \u003cspan\u003e$\u003c/span\u003e3,500 for a simple external FES up to \u003cspan\u003e$\u003c/span\u003e60,000 for a powered mechanical one; (2) the challenge of making them form-fitting, comfortable and lightweight; (3) the inability to customize the placement of sensors as input controls and effectors that optimize user movements; and (4) the lack of rehabilitation professionals skilled in training individuals how they can integrate the orthosis into daily routines [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. To the best of our knowledge, no currently available commercial product offers individuals affordability, comfort, ease of use, and the ability to restore UE function during ADLs in \u0026ldquo;real world\u0026rdquo; situations [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAcademically fabricated powered mechanical UE orthoses have their own limitations \u0026ndash; they often need to be fixed to a wheelchair or stationary surface (e.g., a table) [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] or require support from the person\u0026rsquo;s back and shoulders [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] in order to function. Our clinical experience suggests that most individuals would not find such devices practical to use in ADLs and in the community. Soft robotic sleeves [\u003cspan additionalcitationids=\"CR32 CR33 CR34 CR35 CR36\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] provide an alternative to motor-based approaches, however, such sleeves are not easy to don and doff, and most require an air compressor or compressed gas tank to function. Hence, soft robotic sleeves may not easily find their market without first addressing their practicality and usability issues.\u003c/p\u003e \u003cp\u003eTo overcome the limitations with the currently available UE orthoses, the next generation of UE devices must be simple to use to encourage acceptance and integration in ADLs, while being affordably priced for widespread adoption. Specifically, a user-friendly orthosis would be comfortable, form-fitting, easy to don and doff, and would offer the individual a variety of options for controlling it. Furthermore, it would be lightweight; this is paramount because continuous usage of heavy UE orthoses may have a detrimental effect on user satisfaction and compliance and may contribute to physical problems such as pressure point formation, muscular fatigue, perspiration, and skin irritation [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. These numerous requirements cannot be met in devices that are designed following the \u0026ldquo;one-size fits all\u0026rdquo; principle, without accounting for the unique needs of each individual.\u003c/p\u003e \u003cp\u003eWith this in mind, this study introduces the design, development, implementation, and clinical validation of the NuroSleeve, a novel user-centric active UE orthosis. The NuroSleeve design accommodates the unique needs and conditions of individuals by integrating (1) a user-specific control mechanism, (2) a custom 3D-printed, lightweight and easy to don and doff splint, and (3) an external FES unit. Our goal in developing the NuroSleeve is to meet the unique needs of individuals and to promote the adoption of the technology in clinical settings, at home, and in the community.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eThe NuroSleeve comprises five main components: a custom 3D-printed splint, an external FES unit, a main control unit (MCU), a clinical software suite for configuration, and a rechargeable battery, as shown in Fig.\u0026nbsp;1. The custom firmware running on the MCU receives signals from one or more input sensors, Fig.\u0026nbsp;1: The NuroSleeve consists of the main control unit (center) which accepts different input control signals (left) to control one or more end effectors (right). Implementations are customized for each patient by the occupational therapist using the clinical configuration software.\u003c/p\u003e \u003cp\u003eprocesses the data in real time, and derives control signals for the effectors. The NuroSleeve firmware and hardware allow for user-specific sensor setup combined with personalized input/output mapping. In other words, sensor placement and user commands are customized for the user, as are the effector control strategies. The NuroSleeve can be controlled by one or more of the following control inputs: joystick input, electromyography (EMG) signals, inertial measurement unit (IMU) signals, and voice control. Current effector options include a mechanically operated forearm splint and an external two-channel clinical-grade FES device (see Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eIt is important to emphasize that the NuroSleeve device is user-specific and is personalized with the help of an occupational therapist (OT) using the clinical configuration software. The OT can exploit rehabilitation therapy principles to help identify the optimal combination of sensor inputs and effectors, and the optimal placement of each, based on the individual\u0026rsquo;s unique abilities, needs, and functional goals. The clinical software suite permits these configurations via Bluetooth and allows for device usage monitoring, real-time data collection and visualization, and command exchange between NuroSleeve and external devices, such as brain-computer interface (BCI) systems.\u003c/p\u003e \u003cp\u003eThe NuroSleeve splint is also customized for each individual using 3D scanning and printing technologies. Each splint is built to perfectly accommodate the unique anatomy and impairment of the user to maximize comfort, efficacy, and fit. We refer to this customization process as the \u0026ldquo;Digital Orthotist\u0026rdquo; process, as it combines modern industrial design techniques with occupational therapy and orthotics know-how. The process starts with a 3D scan of the user\u0026rsquo;s impaired hand and forearm, which is then used to build a custom computer-aided designed (CAD) model of the splint. The model may be fine-tuned to suit the user as necessary and then it is 3D printed. The combination of 3D scanning and 3D printing technologies has facilitated our development of an orthosis that is lightweight, aesthetically pleasing, and form-fittingin key locations while form-adjusted in others to avoid pressure points and bony prominences [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The splint has an innovative clamshell design, incorporating a hinge on one side that allows the thumb and cuff sections to be opened and closed, maximizing the individual\u0026rsquo;s ability to don and doff without assistance. The use of 3D-printed rigid plastic components, rather than fabric or other soft materials, provides mechanical support and enables dynamic grasp properties, which are particularly relevant for individuals with spasticity (e.g., excessive tone) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe NuroSleeve orthosis also integrates an external FES unit that can generate functional movement by stimulating paretic muscles. The application of electrical current to a person's muscles depolarizes peripheral neurons and elicits muscle contractions, allowing the person to perform a volitional movement. FES has evolved into a crucial treatment approach that clinicians may use to help individuals with stroke and SCI regains the capacity to stand, walk, reach, and grasp [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. FES can benefit individuals by substituting or enhancing movement. Repeated muscle activation using FES may also increase voluntary motor control. This suggests that the use of FES devices improves motor recovery and can serve as a rehabilitation technique as well as assisting with ADLs [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The NuroSleeve is intended to be used as an assistive device, but it can be also used as a self-modulated rehabilitation device. Supplementary Table\u0026nbsp;1 lists current commercially available neuromuscular electrical stimulation devices designed for rehabilitation purposes.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section3\"\u003e \u003ch2\u003eDevice Control Method\u003c/h2\u003e \u003cp\u003eThe NuroSleeve can control the linear actuator of the splint and/or the FES unit using any of the following control modes: (1) Manual control. A small joystick is fitted to the device at an accessible location for the user; (2) Voice Activation. A voice recognition module that does not require connection to the internet (this was added to the system following user feedback). This voice recognition module can extract and analyze the voice features of a speaker after a single calibration session with the individual. Following the calibration and setup session, the individual can use the voice control option to control the NuroSleeve independently and without the use of external resources; (3) EMG control. The device\u0026rsquo;s two EMG channels can be set up to control the linear actuator and/or FES with a multi-threshold approach, in which one or two signal thresholds are set up to trigger the effectors. The threshold values and their use in controlling the effectors can be customized via the clinical software suite; and/or (4) IMU control. The NuroSleeve can leverage up to two IMUs for splint and/or FES control. In IMU mode, the device can be operated in two different configurations: continuous or discrete. Continuous control configuration uses a multi-threshold approach and makes use of the IMU's 3D orientation data to continuously control the linear actuator and/or FES effectors. The discrete control configuration uses a tap-and-go control approach, in which the system uses the IMU 3D acceleration data to fully open or close the hand; each tap on the IMU sensor toggles between extraction and retraction of the linear actuator and/or FES stimulation. In other words, the IMU sensors can function as a toggle switch to control a two-state machine based on the status of the effector.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eThe Splint\u003c/h2\u003e \u003cp\u003eFigure 2: Exploded view of NuroSleeve splint components including thumb, fingers, arm, and cuff sections.\u003c/p\u003e \u003cp\u003eThe NuroSleeve 3D printed custom splint consists of four main sections: forearm, cuff, thumb, and fingers, as shown in Fig.\u0026nbsp;2. The fingers section facilitates the opening and closing of the hand and is assisted by a splint-mounted low-profile, lightweight electro-mechanical linear actuator (PA-07, Progressive Automations, Arlington, WA) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The linear actuator has a 50mm stroke length and an integrated current limiting circuit as a safeguard mechanism to avoid overtravel. The stationary part of the linear actuator is connected to the forearm section while the actuated rod is connected to the fingers section (see Fig.\u0026nbsp;2). When the linear actuator rod is extended forward, the finger piece assists the user with grasping, when the rod is retracted, it assists with hand opening. This allows the user to achieve functional flexion and extension of the metacarpophalangeal (MCP) joint of the affected hand. The forearm section of the splint has multiple endpoint modification holes for mounting the linear actuator so that its position can be adjusted. This allows for changing the start and end position of the MCP joint\u0026rsquo;s flexion and extension while keeping the range of motion (ROM) fixed. This approach allows the OT to customize the individual\u0026rsquo;s ROM endpoints, based on their clinical conditions and functional needs. Moving the linear actuator distally along the forearm, for instance, enables the user to grasp smaller objects, whereas mounting the linear actuator proximally can facilitate the grasping of larger objects. As part of the NuroSleeve calibration process, safe and optimal hand motion and grasp are carefully verified and validated by an OT to avoid any potential for injuries, such as repeated hyperflexion or hyperextension of fingers and soft tissue injuries [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eDigital Orthotist Process\u003c/h2\u003e \u003cp\u003eTo create a user-centric device that effectively matches the user's hand anatomy and functional requirements, we devised a digital splint design process that combines modern industrial design and occupational therapy techniques. This \u0026ldquo;digital orthotist\u0026rdquo; process (as shown in Fig.\u0026nbsp;3) begins with a 3D scan of the subject\u0026rsquo;s forearm and hand using the Creaform Go!SCAN 3D scanner [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], which features a volumetric accuracy [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] of 0.050 mm\u0026thinsp;\u0026plusmn;\u0026thinsp;0.150 mm/m [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and uses proprietary software (VXmodel) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] to create a watertight model by removing scan artifacts and superfluous information (e.g., chest-related data), overlapping or coarse surfaces, and holes. Once created, the individual watertight model is then imported into Rhinoceros [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], a 3D CAD software that features powerful design and modeling tools ideal for the creation of the custom 3D-printable UE splint. To improve the reliability and repeatability of the \"digital orthotist\u0026rdquo; process, automation scripts are created within Grasshopper [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], a parametric programming tool and native plugin of Rhinoceros. While some common design elements, such as the hinge, endpoint modification holes, and joystick housing can be rescaled and modified for use in multiple models, the profile of the forearm, cuff, thumb, and fingers section of each model are unique, custom-designed by processing the user\u0026rsquo;s UE 3D scan data.\u003c/p\u003e \u003cp\u003eOnce the splint customization and creation have been completed, the 3D splint files are printed on a Markforged X7 industrial 3D printer [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] using the Onyx\u003csup\u003e\u0026trade;\u003c/sup\u003e micro carbon fiber-filled nylon [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Compared to other 3D printing materials, such as Nylon or Acrylonitrile Butadiene Styrene (ABS), Onyx\u003csup\u003e\u0026trade;\u003c/sup\u003e produces orthoses with superior chemical resistance, rigidity, and flexural stress [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. All sections of the splint are printed such that the skin-contact surfaces are face up and thus not in contact with the build\u0026rsquo;s support scaffold. This ensures that the skin-contact surfaces are as smoothed as possible to reduce skin irritation. Printing a complete NuroSleeve splint requires approximately 48 hours.\u003c/p\u003e \u003cp\u003eAfter printing and assembly of the splint, fabric and straps are added at specific locations to secure the user\u0026rsquo;s forearm, hand, and fingers in place. Namely, custom Oly Fun fabric wraps are attached to the finger piece and thumb piece to create a mitten-like pocket for the fingers, Oly Fun fabric was chosen because it is non-stretchy, Fig.\u0026nbsp;3: The \u0026ldquo;Digital orthotist\" process begins with a 3D scan of the individual's hand and forearm. The resulting 3D mesh is then processed and imported into Rhinoceros, where with the help of custom Grasshopper scripts is converted into a personalized 3D-printable splint. Finally, the 3D-printed splint is built and assembled.\u003c/p\u003e \u003cp\u003eallowing the fingers to stay open despite resistance, and it is non-woven, so it does not fray like other fabrics. It also breathes well, which reduces sweat and the likelihood of skin irritation. Finally, Rolyan straps and hook-and-loop tapes were used to secure the cuff and thumb sections to the forearm, preventing the clamshell hinge from opening. Rolyan straps, which are recognized for their softness and flexibility, were chosen to reduce the risk of causing skin irritation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eThe Functional Electrical Stimulation\u003c/h2\u003e \u003cp\u003eAs depicted in Fig.\u0026nbsp;1, for FES, the NuroSleeve incorporates a two-channel commercially available neuromuscular stimulator, the Chattanooga Continuum\u003csup\u003e\u0026trade;\u003c/sup\u003e [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The stimulator can be controlled by any of the input control signals of the NuroSleeve. By stimulating the individual's specific muscles electrically, it is possible to generate retraction or extraction at the relevant joint. The OT can alter the intensity of stimulation based on the individual's body structure and the specific muscle being stimulated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eThe NuroSleeve Main Control Unit\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe MCU enables control of the effectors by the various control sensors. Its core component is an Arduino Nano controller module [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] with an ATMega328p [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] microcontroller, which runs the NuroSleeve firmware and allows for data collection from up to two wired Bosch BNO055 [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] intelligent 9-axis IMUs ( for motion control), up to two MyoWare 2.0 Muscle Sensors [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], (for EMG control), an ELECHOUSE Voice Recognition Module V3 [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] (for voice control) and/or a small joystick controller (for manual control) A description of the device control logic and operating principles are provided in the section below titled \"Multi-threshold Control Approach\".\u003c/p\u003e \u003cp\u003eBluetooth connectivity between the clinical software and external devices, such as BCI systems, has been implemented into the MCU via the onboard DSD TECH HC-05 [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] Bluetooth module, and the NuroSleeve proprietary Bluetooth communication protocol allows easy integration of third-party applications. The NuroSleeve device (including the linear actuator and the MCU) is powered by a single TalentCell 12V 3000mAh Lithium-ion (Li-ion) battery pack [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], consisting of three 18650 Li-ion batteries in series. To ensure adequate electrical safety, the battery pack has an integrated circuit for protection against over-charging, over-discharging, and short circuits.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eClinical Software Suite\u003c/h2\u003e \u003cp\u003eThe Python-based clinical software suite has been developed in-house to provide real-time management and configuration of the NuroSleeve system via Bluetooth. The software features two separate versions: a Clinical Software Suite and a User Software Suite. The Clinical Suite is designed to be used by a trained therapist and can be used to (1) customize input and output mapping; (2) adjust sensitivity and use of the input sensors; (3) visualize sensor data and settings in real-time; and (4) access and store the user compliance data from the MCU. The user suite is intended for home usage by individuals and their caregivers; it has less functionality than the Clinical Suite but permits the user to adjust the sensitivity of the sensors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eUser Compliance Data Monitoring\u003c/h2\u003e \u003cp\u003eThe NuroSleeve is capable of logging user compliance data and storing it in a dedicated flash memory chip inside the MCU. This feature allows therapists and clinicians to monitor at-home device use between clinical appointments, and enabling Remote Therapeutic Monitoring (RTM), for which the U.S. Centers for Medicare and Medicaid Services (CMS) recently established payment policies [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The monitored compliance data can include the total time of device use and the amount of time spent opening and closing the hand and the time spent in each operation mode (i.e., joystick, voice, IMU, EMG), since the clinician\u0026rsquo;s last reset. These data which can help inform therapy goals and outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eMulti-threshold Control Approach\u003c/h2\u003e \u003cp\u003eThe control strategy of the NuroSleeve can be customized to the individual's physiological needs and preferences through a quick calibration and setup phase integrated into the clinical software suite. The primary customization involves the mapping between selected input control signals (sensors) and desired outputs (effectors). Together, the individual and the treating therapist can determine which of the available inputs is most effective in controlling the effectors for that individual. If IMU inputs are selected, the sensors can be configured for continuous or toggle control. From there, the therapist and the individual can select the optimal sensor placement and activation movement for effector control. For continuous control, the effectors will be controlled by the threshold crossings of two custom-determined thresholds of the selected input signal (higher threshold and lower threshold). A positive crossing of a higher threshold triggers an effector command, while a negative crossing of a lower threshold triggers the opposite command. When the signals fall between two thresholds, the effector maintains its current state. The following equations describe how a selected sensor channel can determine the output command to a selected effector.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$Effector\\: Command\\left(t\\right)=\\left\\{\\begin{array}{c}OPEN,\\: if(Sig\\left(t\\right)\u0026gt;HighThr) \\\\ CLOSE,\\: if(Sig\\left(t\\right)\u0026lt;LowThr) \\\\ HOLD,\\: if\\left(LowThr\\le Sig\\left(t\\right)\\le HighThr\\right),\\end{array}\\right.$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(Sig\\left(t\\right)\\)\u003c/span\u003e \u003c/span\u003e is the current input signal channel (sensor) value at time t\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(HighThr\\)\u003c/span\u003e \u003c/span\u003e is a fixed higher threshold value configured with the software\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(LowThr\\)\u003c/span\u003e \u003c/span\u003e is a fixed lower threshold value configured with the software\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(OPEN, CLOSE and HOLD\\)\u003c/span\u003e \u003c/span\u003e are the possible output commands at time t\u003c/p\u003e \u003cp\u003eIf discrete control is selected, the NuroSleeve\u0026rsquo;s effectors are controlled with the IMU sensor acting as a toggle switch. In this configuration, the IMU signal of interest is acceleration and threshold crossing of a single threshold is used to change the state of the effector (OPEN/CLOSE for motor, ON/OFF for FES). This setup is ideal when the user desires to trigger the opening or closing of their hand by tapping the IMU sensor.\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$Effector\\: Command\\left(t\\right)=\\left\\{\\begin{array}{c}FULLY\\: OPEN,\\: if(Status==CLOSED\\: AND\\: Sig\\left(t\\right)\u0026gt;Thr)\\\\ FULLY\\: CLOSE,\\: if\\left(Status==OPEN\\: AND\\: Sig\\left(t\\right)\u0026gt;Thr\\right) \\end{array}\\right.$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIt is important to emphasize that even in the discrete control mode configuration, the device control commands are updated continuously, namely, a new direction command is generated and sent to the effector at every firmware runtime update (time step\u0026thinsp;=\u0026thinsp;20ms).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003eNon-clinical Testing\u003c/h2\u003e \u003cp\u003eA battery of electrical and mechanical bench tests was conducted with the NuroSleeve to ensure that its specifications met the device requirements. The requirements evaluated included hand splint ROM, grasp force and speed, battery life, and total life cycle of the splint. While manual measurements were carried out for most requirements, accelerated life testing was also implemented using two specific setups as shown in Fig.\u0026nbsp;5. The first accelerated life test focused on the mechanical characteristics of the device, repeatedly opening and closing the hand onto a simulated test load placed below the palm to simulate object grasping. The repeated hand movements (opening/closing) were programmed to last four seconds each, while two seconds of rest were introduced between consecutive movements, resulting in a 66% linear actuator utilization (duty cycle). To fully automate the test, two force sensors and a microcontroller were integrated into the test setup to continuously monitor the device operation and collect data, including identifying the breaking point accurately.\u003c/p\u003e \u003cp\u003eThe second accelerated life test deployed a similar setup with the addition of two springs connected to the splint finger piece. The purpose of the springs was to induce a constant load of 13.3N in both extension and flexion to replicate the realistic hand movement force and effect of a spastic hand (which is opposed to extension at the MCP joint), which may decrease the splint's lifespan.\u003c/p\u003e \u003cp\u003eFigure 5: Test Bench for the NuroSleeve with added resistance with springs\u003c/p\u003e \u003cp\u003eTo determine the battery life of the NuroSleeve, its power consumption was analyzed. In standby or FES mode, the NuroSleeve PCB with all sensors connected consumes 175mA of continuous current; movement of the linear actuator increases the current consumption to between 275mA to 375mA, depending on the torque generated. Assuming a nearly linear relationship between battery capacity and operating time due to the extremely low discharge current rate [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], the battery life of NuroSleeve is estimated to be between 8 and 17 hours.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eClinical Trial\u003c/h2\u003e \u003cp\u003eIn addition to the extensive non-clinical bench electrical and mechanical testing, the NuroSleeve has been evaluated in a clinical setting by various stakeholders including users, therapists, caregivers, and physicians. Continuous integration of stakeholder feedback is crucial to the development of a device with practical utility. The NuroSleeve is currently being evaluated in a clinical trial (NCT04798378), approved by the Thomas Jefferson University Institutional Review Board (IRB). Consented and enrolled participants complete an 8-week rehabilitation program that incorporates the device into occupational therapy sessions and ADLs at their homes.\u003c/p\u003e \u003cp\u003eIn brief, the trial consists of an initial (pre-intervention) clinical outcome assessment session, which establishes a baseline of each participant\u0026rsquo;s UE functional ability. The Canadian Occupational Performance Measure (COPM) [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] is also administered to identify three to five activities across multiple domains (including work, self-care, and leisure) in which the participant desires to improve their functional performance or satisfaction. Each participant then undergoes 3D scanning and receives a customized NuroSleeve, after which they engage in eight weeks of outpatient occupational therapy sessions that incorporate the device. During the sessions, the OT trains the participant on how to incorporate the NuroSleeve into their selected activities at home, so they start to use the NuroSleeve independently during daily activities. After the 8-week intervention period, the standardized outcome assessments are repeated, with and without the device being worn.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThis section details the NuroSleeve evaluation results for (1) pre-clinical bench testing and (2) clinical outcomes.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePre-clinical Bench Testing\u003c/h2\u003e \u003cp\u003e Accelerated life testing revealed that the linear actuator was the mechanical component most likely to fail. During testing in both test scenarios (with and without tension springs), the linear actuator failed before any of the 3D-printed components failed or exhibited any signs of wear and mechanical fatigue. The linear actuator failed after 86 hours of continuous operation (totaling 26361 actuations) in the first accelerated life test that simulated grasping an object and after only 47 hours (totaling 14269 actuation) in the second test under constant load, with the additional 13.3 N spring force. As expected, the test with the springs caused the linear actuator to fail in almost half of the time, due to the increased torque requirements. In both tests, the linear actuator stopped working due to the failure of the internal gearbox, which resulted in a higher than nominal current draw of the direct current (DC) motor and eventually triggered the linear actuator\u0026rsquo;s onboard safety power cut-off circuitry. Despite the linear actuator failure preventing the NuroSleeve from being functional, such a failure mode poses no risk to the user and can therefore be categorized as a safe failure. In both accelerated life tests, the linear actuator duty cycle (ratio between the actuation and stationary time durations) was 66% (4 seconds on, 2 seconds off), which is much greater than the 10%-20% nominal duty cycle specified for the PA-07 linear actuator [65]. Utilizing this linear actuator with high-duty cycles leads to excessive operational temperatures and mechanical wear, which can eventually lead to premature failure. Based on these initial findings, additional testing will be performed to better characterize the device's expected life span and maintenance intervals.\u003c/p\u003e \u003cp\u003eThe NuroSleeve\u0026rsquo;s battery life was tested with continuous extension and flexion movement lasting for 4 seconds with a 2-second rest in between. An important requirement for an effective UE orthosis that may be effectively incorporated into ADLs is to operate for more than 8 hours on a single battery charge. With no external loading, the battery life was 13 hours; with a constant load of 13.3 N, the battery life was 11 hours. These results are better than the anticipated (calculated) battery life because the linear actuator in these tests was not operating at maximum torque. Initial clinical trial findings indicate that the NuroSleeve\u0026rsquo;s battery in real-life usage is substantially longer, with participants only needing to recharge the battery once a week. This discrepancy is likely because the linear actuator\u0026rsquo;s \u0026ldquo;real-life\u0026rdquo; duty cycle is much lower than those tested on the bench, and depends upon the wearer\u0026rsquo;s flexion and extension rate, body size, and level of spasticity/tone in their hand.\u003c/p\u003e \u003cp\u003eDepending on the individual's hand size, the splint weighs between 175g and 310g, the control unit weighs 310g, and the FES system weighs 200g. The NuroSleeve has been designed to address the limitations of currently available commercial orthoses.\u003c/p\u003e \u003cp\u003e Table\u0026nbsp;1 compares some characteristics of commercially available UE mobility-assistive devices to those of the NuroSleeve, showing how the latter overcomes most of the common limitations. The NuroSleeve has been designed to be affordable and priced under \u003cspan\u003e$\u003c/span\u003e5,000. For reference, Table\u0026nbsp;2 introduces an itemized list and cost of the components, which total about \u003cspan\u003e$\u003c/span\u003e900 (not including labor or the cost of the machine shop facility and equipment).\u003c/p\u003e \u003cp\u003eThe performance testing results demonstrate that the device has met the desired technical and functional requirements. The above-mentioned properties combined with a lightweight (less than 310g) and custom-fitting splint ensure that the NuroSleeve device can be easily used by people with UE impairment during ADLs and can help them become more independent in both the home and community settings.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003eClinical Trial Outcomes\u003c/h2\u003e \u003cp\u003eFigure 6: Performance and satisfaction scores on the COPM for NS1, NS3, NS4, NS6, NS7 (Per. = Performance, Sat. = Satisfaction). COPM was performed three times, once at the beginning of the trial and twice at the end of the trial with and without the device. The bars represent COPM scores. The black bars are for the pre-trial scores (baseline), the pink bars are for the post-trial scores without the device, while the blue bars are for the post-trial scores with the device.\u003c/p\u003e \u003cp\u003eAt the time of this report, five individuals with hemiparesis from chronic stroke have completed participation in the NuroSleeve clinical trial. The trial intervention comprises three one-hour occupational therapy sessions per week and daily home use of the NuroSleeve, for a total of 8 weeks. The primary clinical outcome measure is the COPM [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], for which we report results in Fig.\u0026nbsp;6. Secondary outcome measures include the Action Research Arm Test (ARAT) [\u003cspan additionalcitationids=\"CR67\" citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], Box and Blocks Test (BBT) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], ABILHAND [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e], and the Patient-Reported Outcomes Measurement Information System UE Short Form Version 2.0 (PROMIS UE SF V2.0) [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]; however, results of these will be reported in a separate paper. All outcome measures are administered both before and after the eight-week intervention. In the post-intervention evaluation, each measure is administered with and without the NuroSleeve. The COPM is a self-reported measure, so for each self-selected task, the participant rates their ability to perform it and satisfaction with performing it. They rate it on an ordinal scale ranging from \u0026ldquo;1\" (cannot do/not satisfied) to \"10\" (can perform well/very satisfied), both before and after the trial intervention. A two-point increase in score indicates a clinically meaningful improvement. Results from the first five trial participants (NS1, NS3, NS4, NS6, and NS7) are reported in Fig.\u0026nbsp;6.\u003c/p\u003e \u003cp\u003eAll five participants were successfully fitted with a customized NuroSleeve and participated in all 24 occupational therapy sessions over 8 weeks. All participants learned how to don and doff the NuroSleeve on their own and were able to use the device at home. Most importantly, all but one participant improved on the primary outcome measure and provided valuable feedback to guide future design improvements. Although myoelectric control was available, all participants and their OTs found the joystick and IMUs to be a more reliable and practical control mode. All participants used IMU-controlled NuroSleeve in their homes without requiring additional calibration or adjustments, providing evidence that this control method is reliable and practical [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Based on the trial participants\u0026rsquo; feedback and our experience with other devices, the IMU control method appears to be more reliable, more consistent, and easier to use than the EMG one.\u003c/p\u003e \u003cp\u003eThe clinical findings shown in Fig.\u0026nbsp;6 demonstrate that all participants reported improvement in the performance of, and satisfaction with, most of their self-identified goals when the device was in use. For many participants, the improvement was clinically meaningful; in three of four goals chosen by NS1, one of three identified by NS3, six of eight identified by NS4, and three of five identified by NS7, improvement exceeded the two-point threshold for a clinically meaningful change. NS6 did not have any clinically meaningful change. Both NS1 and NS7 reported performance and satisfaction scores of 9 while using the device \u0026ndash; close to the maximum score of ten.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe integration of 3D scanning and 3D printing technologies into orthosis manufacturing has paved the way for the creation of custom, form-fitting orthoses that meet the user's anatomical and functional needs. Studies indicate that the comfort and effectiveness of 3D-printed orthoses surpass those of conventional orthoses [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. In addition to being more comfortable and effective, 3D-printed orthoses are lighter in weight and more affordable; all of these advantages are at the core of NuroSleeve\u0026rsquo;s design approach [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe current NuroSleeve is the result of several iterations based on the feedback received from study participants and OTs as part of the ongoing clinical trial. The primary design changes implemented thus far include: (1) the 3D model was altered by removing material at the wrist to avoid contact with bony prominences; (2) the thumb and cuff pieces were separated into two distinct pieces, allowing the user to more easily don and doff the splint; (3) the joystick controller has been mounted onto the splint making it more convenient for the user to control the device with their unimpaired hand. We found this to be extremely helpful for individuals who rely on their unaffected hand to support and move their impaired arm; since the unimpaired hand typically provides support in the proximity of the contralateral forearm, placing the joystick in this area allows for quick and easy access to it. Although, the NuroSleeve can be controlled by EMG signals, which are highly correlated with voluntary UE movements, based on previous studies [\u003cspan additionalcitationids=\"CR76\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], our experience, and participant feedback, EMG signals tend to be erratic, so this is the least preferred control method.\u003c/p\u003e \u003cp\u003eAlthough the clinical results presented are from a small cohort of participants in a feasibility study, it should be noted that there is no plausible physiologic or physical process by which random chance would account for the functional improvements seen in these participants: all of them had been living with chronic deficits for two or more years following a stroke and had already exhausted standard rehabilitation therapy. Most importantly, each served as their own control and compared function with and without the device, demonstrating that the benefits were due to the device, not a non-specific mass practice effect. The functional improvements observed merit a prospective, randomized, controlled trial, with an adequate sample size to be able to differentiate the relative contributions of traditional rehabilitation therapy alone, traditional rehabilitation with the NuroSleeve, and abbreviated rehabilitation with the NuroSleeve. In addition to the promising preliminary findings, this trial demonstrates a successful model for the future of UE rehabilitation methods, an interdisciplinary approach where a team comprised of neurology, engineering, software development, industrial design, and occupational therapy professionals collaborate to design and create a customizable, durable, affordable, and genuinely functional assistive device.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eLoss of independence due to UE neuromuscular impairment represents a high socio-economic burden for society. Current rehabilitation methods and commercially available UE active orthoses seem to be limited in their ability to restore function and thus improve independence in individuals living with UE impairment. The NuroSleeve has been designed, developed, and clinically validated to address these limitations.\u003c/p\u003e \u003cp\u003eThe NuroSleeve is an innovative user-centric 3D-printed UE active orthosis and closed-loop FES system that improves function and independence in ADLs of individuals living with UE neuromuscular impairment. To overcome the limitations of existing neurotechnology, the NuroSleeve deploys 3D printing and introduces a design that is user-centered, lightweight, affordable, easy to don and doff, and user-friendly. Furthermore, the NuroSleeve implements innovative options for control methods (inputs) and effectors (outputs) that can be customized and used in various combinations and result in a functionally and clinically effective active orthosis for both home and clinical use. Current control methods include manual, EMG, IMU, and voice controls, while the effectors include a linear actuator that opens and closes the hand and two channels of FES. The team will continue its research and development activities to improve upon the device design and functionality; for example, work is underway to incorporate an elbow brace into the NuroSleeve, which would provide the user more degrees of freedom (DOF), particularly arm flexion and extension. We also aim to make the control sensors wireless and to improve the battery life so the user may operate it for longer time without needing to recharge.\u003c/p\u003e \u003cp\u003eThe NuroSleeve was pre-clinically evaluated using state-of-the-art bench testing to ensure adequate performance, safety, and quality of metrics. Bench test results demonstrate that the NuroSleeve meets all of its technical objectives and operational requirements, due to its customizable and flexible hardware and firmware designs. Preliminary findings of the clinical trial reveal that NuroSleeve meets its clinical objectives and addresses previously unmet clinical needs. The NuroSleeve has shown benefit to the individuals who have enrolled in the ongoing trial; however, it can only become beneficial and available to the large population of individuals living with UE impairment if it becomes a commercially available FDA-cleared medical device. To achieve this goal, a product development plan is in place, which includes: an FDA-compliant Quality Management System, a redesign and optimization, further bench testing to meet all FDA requirements, and a subsequent pivotal clinical trial. Such steps will ensure that future iterations of the NuroSleeve may be available to more individuals with UE impairment and potentially become part of clinical care.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e3D\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethree dimensional\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eupper extremities\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003espinal cord injury\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDMD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDuchenne Muscular Dystrophy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBecker Muscular Dystrophy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADLs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eActivities of Daily Living\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emuscular dystrophy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFES\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFunctional Electrical Stimulation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emain control unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEMG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eelectromyography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIMU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einertial measurement unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoccupational therapist\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebrain computer interface\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomputer-aided design\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emetacarpophalangeal\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erange of motion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eABS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcrylonitrile Butadiene Styrene\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFDA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFood and Drug Administration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eelectromagnetic interference\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprinted circuit board\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLi-ion\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLithium-ion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRTM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRemote Therapeutic Monitoring\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMedicare and Medicaid Services\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIRB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInstitutional Review Board\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOPM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCanadian Occupational Performance Measure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edirect current\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eARAT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAction Research Arm Test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBBT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBox and Blocks Test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePROMIS UE SF V2.0\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePatient-Reported Outcomes Measurement Information System UE Short Form Version 2.0\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDOF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edegrees of freedom\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study has been approved by the Institutional Review Board at Thomas Jefferson University. All participants provided written informed consent before participating.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eM.D.S., A.N., and M.A. are inventors on a US provisional patent application that has been filed by Thomas Jefferson University on the methods described in this paper. All other authors report that they do not have any conflicts of interest with the research described.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research was supported by philanthropy to the Farber Institute of Neuroscience at Thomas Jefferson University.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; Contributions\u003c/p\u003e\n\u003cp\u003eA.N. leads and oversees the design and production of NuroSleeve, while M.D.S. designed and oversees the clinical trial. M.A. designed the splint pieces and optimized the 3D model. M.K. designed the circuitry, P.A. wrote the device software and firmware, and R.M.Z. designed the MCU housing and oversaw 3D printing and device assembly. R.M.Z. and M.K. designed the bench tests and tabulated results, and E.H. provided the clinical outcomes. N.S. assisted with the literature review, reference management and review of the manuscript. A.N. and M.K. directed the preparation of the manuscript, to which all authors contributed. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank the members of the Center for Neurorestoration for their assistance with and dedication to this endeavor, particularly Erica Jones for support with trial logistics, Joe Kardine for developing the occupational therapy protocol optimally suited for the NuroSleeve, and Saami Zakaria for helping to integrate the voice recognition module into the device. They acknowledge the contributions of Drs. Mary Jane\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u0026ldquo;MJ\u0026rdquo; Mulcahey and Namrata Grampurohit towards trial design, and Dr. Robert H. Rosenwasser for continual support at the institutional level. The authors want to recognize Dr. Iyad Obeid and Michelle A. Keon for general advice and content editing respectively. Finally, the authors greatly appreciate each participant\u0026rsquo;s time and engagement in the study, especially during the pandemic.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eO\u0026rsquo;Neill C, Proietti T, Nuckols K, Clarke ME, Hohimer CJ, Cloutier A, et al. Inflatable Soft Wearable Robot for Reducing Therapist Fatigue During Upper Extremity Rehabilitation in Severe Stroke. IEEE Robot Autom Lett. 2020;5:3899\u0026ndash;906.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStroke Facts \u0026amp; Statistics. Stroke Awareness Foundation. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.strokeinfo.org/stroke-facts-statistics/\u003c/span\u003e\u003cspan address=\"https://www.strokeinfo.org/stroke-facts-statistics/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 17 Dec 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllison R, Shenton L, Bamforth K, Kilbride C, Richards D, Incidence. Time Course and Predictors of Impairments Relating to Caring for the Profoundly Affected arm After Stroke: A Systematic Review. Physiother Res Int. 2016;21:210\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDunkelberger N, Schearer EM, O\u0026rsquo;Malley MK. A review of methods for achieving upper limb movement following spinal cord injury through hybrid muscle stimulation and robotic assistance. Exp Neurol. 2020;328:113274.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhat is Muscular Dystrophy? Centers for Disease Control and Prevention. 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/ncbddd/musculardystrophy/facts.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/ncbddd/musculardystrophy/facts.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 4 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarcia-Garcia LA, Rodr\u0026iacute;guez M. Competitive and technology intelligence to reveal the most influential authors and inter-institutional collaborations on additive manufacturing for hand orthoses. J Intell Stud Bus. 2019;8:32\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNorouzi-Gheidari N, Hernandez A, Archambault PS, Higgins J, Poissant L, Kairy D, Feasibility. Safety and Efficacy of a Virtual Reality Exergame System to Supplement Upper Extremity Rehabilitation Post-Stroke: A Pilot Randomized Clinical Trial and Proof of Principle.Int J Environ Res Public Health. 2019;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVirani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, et al. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation. 2021;143:e254\u0026ndash;743.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Miguel-Rubio A, Rubio MD, Alba-Rueda A, Salazar A, Moral-Munoz JA, Lucena-Anton D. Virtual Reality Systems for Upper Limb Motor Function Recovery in Patients With Spinal Cord Injury: Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth. 2020;8:e22537.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYozbatiran N, Francisco GE. Robot-assisted Therapy for the Upper Limb after Cervical Spinal Cord Injury. Phys Med Rehabil Clin N Am. 2019;30:367\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJanssen MMHP, Harlaar J, Koopman B, de Groot IJM. Unraveling upper extremity performance in Duchenne muscular dystrophy: A biophysical model. Neuromuscul Disord. 2019;29:368\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrisafulli S, Sultana J, Fontana A, Salvo F, Messina S, Trifir\u0026ograve; G. Global epidemiology of Duchenne muscular dystrophy: an updated systematic review and meta-analysis. Orphanet J Rare Dis. 2020;15:141.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlock VAJ, Pitsch E, Tahir P, Cree BAC, Allen DD, Gelfand JM. Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review. PLoS One. 2016;11:e0154335.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh H, Unger J, Zariffa J, Pakosh M, Jaglal S, Craven BC, et al. Robot-assisted upper extremity rehabilitation for cervical spinal cord injuries: a systematic scoping review. Disabil Rehabil Assist Technol. 2018;13:704\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLang CE, Bland MD, Bailey RR, Schaefer SY, Birkenmeier RL. Assessment of upper extremity impairment, function, and activity after stroke: foundations for clinical decision making. J Hand Ther. 2013;26:104\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLo AC, Guarino PD, Richards LG, Haselkorn JK, Wittenberg GF, Federman DG, et al. Robot-assisted therapy for long-term upper-limb impairment after stroke. N Engl J Med. 2010;362:1772\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolf SL, Winstein CJ, Miller JP, Taub E, Uswatte G, Morris D, et al. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA. 2006;296:2095\u0026ndash;104.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePage SJ, Levine P, Leonard A. Mental practice in chronic stroke: results of a randomized, placebo-controlled trial. Stroke. 2007;38:1293\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKontson K, Marcus I, Myklebust B, Civillico E. Targeted box and blocks test: Normative data and comparison to standard tests. PLoS ONE. 2017;12:e0177965.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaceira-Elvira P, Popa T, Schmid A-C, Hummel FC. Wearable technology in stroke rehabilitation: towards improved diagnosis and treatment of upper-limb motor impairment. J Neuroeng Rehabil. 2019;16:142.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiloyannis M, Chiaradia D, Frisoli A, Masia L. Physiological and kinematic effects of a soft exosuit on arm movements. J Neuroeng Rehabil. 2019;16:29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIwamoto Y, Imura T, Suzukawa T, Fukuyama H, Ishii T, Taki S, et al. Combination of Exoskeletal Upper Limb Robot and Occupational Therapy Improve Activities of Daily Living Function in Acute Stroke Patients. J Stroke Cerebrovasc Dis. 2019;28:2018\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMyomo, Myomo. https://myomo.com/. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH200 wireless - Bioness. Bioventus. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bionessrehab.com/h200/\u003c/span\u003e\u003cspan address=\"https://bionessrehab.com/h200/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 6 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOmnihi5\u0026trade;. Accelerated Care Plus Corporation (ACP). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://acplus.com/omnihi5\u003c/span\u003e\u003cspan address=\"https://acplus.com/omnihi5\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 6 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBos RA, Haarman CJW, Stortelder T, Nizamis K, Herder JL, Stienen AHA, et al. A structured overview of trends and technologies used in dynamic hand orthoses. J Neuroeng Rehabil. 2016;13:62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahman T, Sample W, Seliktar R, Alexander M, Scavina M. A body-powered functional upper limb orthosis. J Rehabil Res Dev. 2000;37:675\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolley D, Johnson M, Harris G, Beardsley S. A modular low-clearance wrist orthosis for improving wrist motion in children with cerebral palsy. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2014;2014:3069\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorini\u0026egrave;re B, Verney A, Abroug N, Garrec P, Perrot Y. EMY: a dual arm exoskeleton dedicated to the evaluation of Brain Machine Interface in clinical trials. 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2015. p.\u0026nbsp;5333\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKooren PN, Dunning AG, Janssen MMHP, Lobo-Prat J, Koopman BFJM, Paalman MI, et al. Design and pilot validation of A-gear: a novel wearable dynamic arm support. J Neuroeng Rehabil. 2015;12:83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoiliaris P. 3D Printed Soft Fluidic Actuator for an Assistive Hand Exoskeleton Device [Master Thesis]. [Mekelweg, Netherlands]: Delft University of Technology; 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao H, Jalving J, Huang R, Knepper R, Ruina A, Shepherd R. A Helping Hand: Soft Orthosis with Integrated Optical Strain Sensors and EMG Control. IEEE Robot Autom Mag. 2016;23:55\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCho KH, Kim Y, Yang SY, Kim K, Park JH, Rodrigue H, et al. Artificial musculoskeletal actuation module driven by twisted and coiled soft actuators. Smart Mater Struct IOP Publishing. 2019;28:125010.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Tan X, Yan D, Zhang Z, Gong Y. A Composite Fabric-Based Soft Rehabilitation Glove With Soft Joint for Dementia in Parkinson\u0026rsquo;s Disease. IEEE J Transl Eng Health Med. 2020;8:1400110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBae J-H, Kim Y-M, Moon I. Wearable hand rehabilitation robot capable of hand function assistance in stroke survivors. 2012 4th IEEE RAS \u0026amp; EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob). Rome, Italy: IEEE; 2012. p.\u0026nbsp;1482\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatar MNAA, Komeda T, Low CY, Mahmud J. System Integration and Control of Finger Orthosis for Post Stroke Rehabilitation. Procedia Technol. 2014;15:755\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeng W, Sheng B, Klinger M, Liu Q, Zhou Z, Xie SQ. Design and control of a robotic wrist orthosis for joint rehabilitation. 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). Busan, Korea (South): IEEE; 2015. p.\u0026nbsp;1235\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcKee P, Nguyen C. Customized dynamic splinting: orthoses that promote optimal function and recovery after radial nerve injury: a case report. J Hand Ther. 2007;20:73\u0026ndash;87. quiz 88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Y, Li X, Chang Y, Wang Y, Che L, Shi G, et al. Design of Personalized Cervical Fixation Orthosis Based on 3D Printing Technology. Appl Bionics Biomech. 2022;2022:8243128.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarquez-Chin C, Popovic MR. Functional electrical stimulation therapy for restoration of motor function after spinal cord injury and stroke: a review. Biomed Eng Online. 2020;19:34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuandt F, Hummel FC. The influence of functional electrical stimulation on hand motor recovery in stroke patients: a review. Exp Transl Stroke Med. 2014;6:9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMicro Linear Actuator. Progressive Automations. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.progressiveautomations.com/products/micro-linear-actuator?variant=18277344575555\u003c/span\u003e\u003cspan address=\"https://www.progressiveautomations.com/products/micro-linear-actuator?variant=18277344575555\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiese J, Cerniglia C. Soft Tissue Injuries of the Finger and Thumb. Seminars in Ultrasound. CT and MRI. 2018;39:397\u0026ndash;410.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGo!SCAN 3D. (White Light Portable [3D Object Scanner]). Creaform. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.creaform3d.com/en/handheld-portable-3d-scanner-goscan-3d\u003c/span\u003e\u003cspan address=\"https://www.creaform3d.com/en/handheld-portable-3d-scanner-goscan-3d\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChromy A. High-Accuracy Volumetric Measurements of Soft Tissues using Robotic 3D Scanner. IFAC-PapersOnLine. 2015;48:318\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGo!SCAN 3D scanner [technical specifications]. Creaform. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.creaform3d.com/en/handheld-portable-3d-scanner-goscan-3d/technical-specifications\u003c/span\u003e\u003cspan address=\"https://www.creaform3d.com/en/handheld-portable-3d-scanner-goscan-3d/technical-specifications\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVXmodel. : scan-to-CAD software module. Creaform. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.creaform3d.com/en/metrology-solutions/3d-applications-software-platforms/vxmodel-scan-cad-software-module\u003c/span\u003e\u003cspan address=\"https://www.creaform3d.com/en/metrology-solutions/3d-applications-software-platforms/vxmodel-scan-cad-software-module\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcNeel R. Rhinoceros 3D. www.rhino3d.com. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavidson S, Grasshopper. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.grasshopper3d.com/\u003c/span\u003e\u003cspan address=\"https://www.grasshopper3d.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eX7 Industrial Carbon Fiber 3D Printer. Markforged. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://markforged.com/3d-printers/x7\u003c/span\u003e\u003cspan address=\"https://markforged.com/3d-printers/x7\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOnyx - Composite 3D Printing Material. Markforged. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://markforged.com/materials/plastics/onyx\u003c/span\u003e\u003cspan address=\"https://markforged.com/materials/plastics/onyx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMATERIAL DATASHEET Composites - Markforged. Markforged. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://static.markforged.com/downloads/composites-data-sheet.pdf\u003c/span\u003e\u003cspan address=\"https://static.markforged.com/downloads/composites-data-sheet.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 22 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB\u0026aacute;rnik F, Vaško M, S\u0026aacute;ga M, Handrik M, Sapietov\u0026aacute; A. Mechanical properties of structures produced by 3D printing from composite materials. MATEC Web of Conferences. 2019;254:01018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChattanooga\u0026reg;, Continuum. \u003csup\u003e\u0026trade;\u003c/sup\u003e. Chattanooga\u0026reg;. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.chattanoogarehab.com/us/chattanooga-continuumtm-2600-dev\u003c/span\u003e\u003cspan address=\"https://www.chattanoogarehab.com/us/chattanooga-continuumtm-2600-dev\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 11 Dec 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNano | Arduino Documentation. Arduino. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://docs.arduino.cc/hardware/nano\u003c/span\u003e\u003cspan address=\"https://docs.arduino.cc/hardware/nano\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 11 Dec 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eATmega328P. Microchip Technology. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.microchip.com/en-us/product/ATmega328P\u003c/span\u003e\u003cspan address=\"https://www.microchip.com/en-us/product/ATmega328P\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmart sensor BNO055. Bosch Sensortec.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bosch-sensortec.com/products/smart-sensors/bno055/\u003c/span\u003e\u003cspan address=\"https://www.bosch-sensortec.com/products/smart-sensors/bno055/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMYOWARE 2.0 TECH SPECS: Muscle Sensor. MYOWARE by Advancer Technologies. 2022.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://myoware.com/products/technical-specifications/#muscle-sensor\u003c/span\u003e\u003cspan address=\"https://myoware.com/products/technical-specifications/#muscle-sensor\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpeak recognition, voice recognition module V3. ELECHOUSE. 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.elechouse.com/product/speak-recognition-voice-recognition-module-v3/\u003c/span\u003e\u003cspan address=\"https://www.elechouse.com/product/speak-recognition-voice-recognition-module-v3/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDSD Tech HC. -05 bluetooth serial pass-through module wireless serial communication with button for Arduino. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.dsdtech-global.com/2017/07/dsd-tech-hc-05-bluetooth-serial-pass.html\u003c/span\u003e\u003cspan address=\"http://www.dsdtech-global.com/2017/07/dsd-tech-hc-05-bluetooth-serial-pass.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYB1203000\u0026ndash;12V Lithium ion battery. Talentcell Technology Co.,Ltd. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://talentcell.com/lithium-ion-battery/12v/yb1203000.html\u003c/span\u003e\u003cspan address=\"https://talentcell.com/lithium-ion-battery/12v/yb1203000.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHome - Centers for Medicare \u0026amp;. Medicaid Services. CMS.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cms.gov/\u003c/span\u003e\u003cspan address=\"https://www.cms.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 7 Dec 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLain MJ, Kendrick E. Understanding the limitations of lithium ion batteries at high rates. J Power Sources. 2021;493:229690.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonnelly C, O\u0026rsquo;Neill C, Bauer M, Letts L. Canadian Occupational Performance Measure (COPM) in Primary Care: A Profile of Practice. Am J Occup Ther. 2017;71:7106265010p1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMicro Linear Actuator. Progressive Automations. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.progressiveautomations.com/products/micro-linear-actuator?variant=18277344575555\u003c/span\u003e\u003cspan address=\"https://www.progressiveautomations.com/products/micro-linear-actuator?variant=18277344575555\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYozbatiran N, Der-Yeghiaian L, Cramer SC. A standardized approach to performing the action research arm test. Neurorehabil Neural Repair. 2008;22:78\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMathiowetz V, Volland G, Kashman N, Weber K. Adult norms for the Box and Block Test of manual dexterity. Am J Occup therapy. 1985;39:386\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res. 1981;4:483\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePenta M, Thonnard JL, Tesio L. ABILHAND: a Rasch-built measure of manual ability. Arch Phys Med Rehabil. 1998;79:1038\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eResnik LJ, Stevens PM, Ni P, Borgia ML, Clark MA. Assessment of Patient-Reported Physical Function in Persons with Upper Extremity Amputation: Comparison of Short Form instruments drawn from the PROMIS v2.0 Upper Extremity item bank. Am J Phys Med Rehabil. 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/PHM.0000000000002044\u003c/span\u003e\u003cspan address=\"10.1097/PHM.0000000000002044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePROMIS: Patient-reported Outcomes Measurement Information System - home page. National Institutes of Health, U.S. Department of Health and Human Services. 2019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://commonfund.nih.gov/promis/index\u003c/span\u003e\u003cspan address=\"https://commonfund.nih.gov/promis/index\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 30 Dec 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL300 go. Bioness. 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bionessrehab.com/l300\u003c/span\u003e\u003cspan address=\"https://bionessrehab.com/l300\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Nov 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoo YJ, Boudier-Rev\u0026eacute;ret M, Chang MC. 3D printing technology applied to orthosis manufacturing: narrative review. Ann Palliat Med. 2020;9:4262\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu P, Liao Z, Zeng Q, Chen H, Huang W, Liu Z, et al. Customized Three-Dimensional-Printed Orthopedic Close Contact Casts for the Treatment of Stable Ankle Fractures: Finite Element Analysis and a Pilot Study. ACS Omega. 2021;6:3418\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eResnik LJ, Acluche F, Lieberman Klinger S. User experience of controlling the DEKA Arm with EMG pattern recognition. PLoS ONE. 2018;13:e0203987.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie T, Leng Y, Zhi Y, Jiang C, Tian N, Luo Z et al. Increased Muscle Activity Accompanying With Decreased Complexity as Spasticity Appears: High-Density EMG-Based Case Studies on Stroke Patients.Front Bioeng Biotechnol. 2020;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLueken MJ, Misgeld BJE, Leonhardt S. Classification of spasticity affected EMG-signals. 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN). Cambridge, MA, USA: IEEE; 2015. p.\u0026nbsp;1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"assistive, exoskeleton, hand therapy, rehabilitation, stroke, wearable robotics, three dimensional (3D) printed active orthoses, upper extremity impairment","lastPublishedDoi":"10.21203/rs.3.rs-2451365/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2451365/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Active upper extremity (UE) assistive devices have the potential to restore independent functional movement in individuals with UE impairment due to neuromuscular diseases or injury-induced chronic weakness. Academically fabricated UE assistive devices are not usually optimized for Activities of Daily Living (ADLs), whereas commercially available alternatives are prohibitively expensive. Both options are typically difficult to don and doff and are cumbersome for extensive daily use. To overcome these limitations, we have designed, developed, and clinically validated the NuroSleeve, an innovative user-centered UE orthosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This study introduces the design, implementation, and clinical evaluation of the NuroSleeve, a user-centered, lightweight, affordable, easy to don and doff 3D-printed UE active orthosis for improving function and independence in individuals living with UE neuromuscular impairment. Our primary goals are to develop a customized active UE brace that individuals with UE impairment can use to perform ADLs and to evaluate the benefits of incorporating the device into occupational therapy sessions. The trial is designed as a prospective, open-label, single-cohort feasibility study of eight-week sessions combined with at-home use of the device and implements an iterative device design process where feedback from participants and therapists inform future design improvements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e All participants learned how to independently don, doff, and use the NuroSleeve in ADLs, both in clinical therapy and in their home environments. All participants showed improvements in their Canadian Occupational Performance Measure (COPM), which was the primary clinical trial outcome measure. Furthermore, the participants and therapists provided valuable feedback to guide further development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Our results from non-clinical testing and clinical evaluation demonstrate that the NuroSleeve has met performance and safety requirements and effectively improves independent voluntary function during ADLs. The study’s encouraging preliminary findings indicate that the NuroSleeve has met its technical and clinical objectives while improving on the limitations of the existing UE orthoses due to its personalized and flexible approach to hardware and firmware design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration:\u003c/strong\u003e ClinicalTrials.gov identifier: NCT04798378,\u003c/p\u003e\n\u003cp\u003e\u003ca href=\"https://clinicaltrials.gov/ct2/show/NCT04798378\"\u003ehttps://clinicaltrials.gov/ct2/show/NCT04798378\u003c/a\u003e, date of registration: March 15, 2021.\u003c/p\u003e","manuscriptTitle":"The NuroSleeve, A User-Centered 3D Printed Orthosis and Functional Electrical Stimulation System for Individuals with Upper Extremity Impairment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-11 15:36:03","doi":"10.21203/rs.3.rs-2451365/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-04-14T09:01:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-02-27T15:07:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"026d9bcf-31d0-4cda-9d90-d9b798a42b8d","date":"2023-02-14T04:55:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8445bbec-bd22-4513-ae1e-93973708da7b","date":"2023-01-30T13:42:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-01-30T10:59:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33a2d637-b334-41b9-b868-d55b88fe08ad","date":"2023-01-30T10:49:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-01-29T19:37:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-01-09T06:49:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-01-09T06:49:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of NeuroEngineering and Rehabilitation","date":"2023-01-06T17:47:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"baf4f1e7-aaa6-4681-9778-985d7982ad2f","owner":[],"postedDate":"January 11th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T22:19:28+00:00","versionOfRecord":{"articleIdentity":"rs-2451365","link":"https://doi.org/10.1186/s12984-023-01228-2","journal":{"identity":"journal-of-neuroengineering-and-rehabilitation","isVorOnly":false,"title":"Journal of NeuroEngineering and Rehabilitation"},"publishedOn":"2023-08-04 21:51:23","publishedOnDateReadable":"August 4th, 2023"},"versionCreatedAt":"2023-01-11 15:36:03","video":"","vorDoi":"10.1186/s12984-023-01228-2","vorDoiUrl":"https://doi.org/10.1186/s12984-023-01228-2","workflowStages":[]},"version":"v1","identity":"rs-2451365","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2451365","identity":"rs-2451365","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}