Journal of NeuroEngineering and Rehabilitation

There are many alternative methods to joystick control for control of Electric Powered Wheelchairs for users with neuromuscular disabilities, such as muscular dystrophy, and spinal cord injuries, such as tetraplegia. However, these methods- which include the sip-and-puff method, head and neck movement, blinking, or tongue movement- hinder social interaction, and are therefore detrimental to user independence. In recent years, research has explored the use of Electromyography (EMG) signals from alternative muscles to control a powered wheelchair, consequently increasing the quality of life of these users. The Auricular Muscles (AM) may be suitable, as they are controlled separately from the facial nerve and are vestigial in humans, making them advantageous for powered wheelchair control for users with tetraplegia. Additionally, they are located around the ear, adding a level of cosmesis when designing wearable sensors and prosthesis. This paper extracts and implements two control strategies from current literature and, for the first time, compares them directly, demonstrating viable implementation approaches for an online EMG-based powered-wheelchair control system. A Support Vector Machine (SVM) was developed and various window lengths were compared, with the most accuracy and real-time effectiveness found at 300ms. A study with three participants demonstrates the feasibility of these methods of control as well as experimental results to guide the potential AM use.

Conventional therapy after stroke focuses on reducing physical impairments. However, the decisions that guide peoples movements may have far-reaching consequences towards recovery. We lack the tools to characterize these decisions. Recently, researchers have created a quantitative behavioral assessment of effort-based decision-making and applied it to some clinical populations. The purpose of this paper is to examine the feasibility of evaluating effort-based decision-making during walking after stroke. We recruited five neurotypical participants in an initial study. We conducted a subjective effort valuation on the neurotypical individuals with and without a knee immobilizer to simulate the biomechanics of reduced knee flexion during post-stroke gait. Participants cleared obstacles of varying heights during overground walking, followed by rating their perceived effort and then completing an effort choice paradigm to calculate subjective effort value. In a second experiment, we recruited five individuals with stroke to perform a similar protocol without an immobilizer during harnessed treadmill walking. We found that rated perceived effort increased monotonically with obstacle height across groups, that individuals could recall obstacle heights without cues, and that subjective effort value increased with knee immobilization in the control group as expected. We conclude that adapting an effort-based decision-making assessment to a walking context in people with stroke is feasible.

Motor rehabilitation requiring sustained physical exercise faces poor adherence in neurological populations due to insufficient supervision and monotony. While virtual reality and musical biofeedback independently improve engagement and motivation, their comparative and combined impact on intensity control strategies during high-intensity interval training (HIIT) remains unexplored. Thirty healthy adults (16 males, 14 females; mean age 27.5 {+/-} 7.2 years) were sequentially assigned to three feedback modalities (n=10 each) during intensity-guided stationary cycling: visual-only (position-based), musical-only (speed-based), and combined audiovisual (position-based). Participants completed two 9-minute moderate-to-high intensity sessions (Set 1 and Set 2) maintaining pedaling speed within a target speed zone. Performance distinguished control strategy from effectiveness: stability via target zone exits, correction capacity via recovery time and sustained deviations, and overall effectiveness via time in zone. Heart rate (HR) assessed physiological intensity; usability and cognitive workload were evaluated via e-Rubric and NASA-TLX. Distinct regulation strategies emerged. Musical-only showed significantly lower stability (Set 1: 14.52 exits/min vs. 1.48 visual and 1.79 combined; corrected p < 0.0167) but superior correction (0.21s recovery vs. 2.48s and 1.06s; p < 0.0001) with minimal sustained deviations. Combined feedback achieved highest Set 2 effectiveness (98.13% vs. 95.17% time in zone; corrected p < 0.0167) but elevated physical demand (corrected p < 0.0167). HR variability was comparable (p = 0.85), confirming consistent cardiovascular workload despite differing strategies. Satisfaction was high, with slight preference for musical feedback; cognitive workload did not differ. Musical biofeedback promotes reactive control with frequent but rapidly corrected oscillations, maintaining physiological safety and engagement. Visual feedback ensures stable target adherence at the cost of compensatory physical effort. Combined modality offered no synergy, increasing demand without improving effectiveness. Findings reveal a trade-off between stability and correction agility, supporting tailored modality selection: musical feedback suits unsupervised rehabilitation prioritizing engagement, rapid error correction, and sustainable effort, while visual feedback suits supervised protocols requiring stable preventive control and precise adherence quantification. Author summaryMany people undergoing neurological rehabilitation struggle to maintain adherence to high-intensity exercise programs, particularly without direct supervision. While virtual reality and musical feedback have shown promise for improving engagement and motivation, we didnt know which type works best for controlling exercise intensity, or whether combining them would be better. We tested three feedback systems with 30 healthy adults performing stationary cycling: visual-only, musical-only, and both combined. We measured how well participants stayed within target speed and assessed their experience. Musical feedback prompted frequent but instant adjustments--a reactive strategy that was less physically demanding and most enjoyable. Visual feedback kept participants more precisely in the target zone but required significantly more effort. Surprisingly, combining both didnt improve performance and instead increased physical demand. Our results show that different feedback types suit different rehabilitation contexts. Musical feedback may be ideal for unsupervised home-based exercise because it keeps people engaged without requiring exhausting effort. Visual feedback works better when precise control is essential in supervised clinical settings, despite being more demanding. Combining both offers no advantage. These findings help clinicians choose the right feedback approach based on their specific rehabilitation goals.

PurposeVisual function testing in retinal prosthesis users relies on repetitive psychophysical tasks that are cognitively demanding and fatiguing. Gamification may increase engagement, but its effects on perceptual performance in implanted users remain unclear. MethodsThree Argus II users completed circle localization and motion direction discrimination in clinical and gamified versions. Visual stimuli, trial structure, and response requirements were matched within each participant; gamified versions added scoring, background music, and affectively framed end-of-trial auditory feedback. Difficulty and response format were calibrated to individual abilities (8AFC for two participants; 4AFC restricted to cardinal directions for one participant). ResultsGamification improved accuracy and reduced angular error in localization but did not improve motion discrimination. Effects were task-dependent and varied across participants, with reduced precision in the gamified motion task for one user. Participants preferred gamified localization and reported higher enjoyment and sustained attention; responses to gamified motion were mixed. ConclusionsGamification can influence measured performance and user experience in prosthetic vision testing, but benefits are not universal and depend on task demands and cognitive load, indicating that engagement can affect outcomes in tests often treated as objective. Translational relevancePersonalized, engagement-aware gamified tools with adaptive difficulty may improve the usability and scalability of prosthetic vision assessment and rehabilitation, including at-home training.

BackgroundCommercially-available microprocessor-controlled prosthetic knees are unable to fully replicate the biomechanical function of the missing biological limb. While powered prostheses have the capacity to restore joint level kinetics, current systems rely on intrinsic control schemes that do not allow the user to volitionally modulate movement under neural commands. This limitation may compromise functional performance and hinder prosthetic embodiment, the sense that the device is part of the users body. In a case study on one test participant, we evaluate the functional and perceptual benefits of a bone-anchored, neurally-controlled knee prosthesis by comparing it to the participants microprocessor-controlled prosthesis. MethodsWe conducted a within-subject study on an individual with a transfemoral amputation, with an osseointegrated implant and surgically reconstructed agonist-antagonist muscle pairs. We tested a neurally-controlled powered knee and conventional microprocessor knee across a set of activities, including seated volitional control tasks, sit-to-stand transitions, squatting, level-ground walking, stair ascent, and uninstructed standing. Performance metrics included knee kinematics, prosthesis-generated mechanical power, and functional outcomes such as gait speed, stair ascent time, and weight-bearing symmetry derived from ground reaction forces. Functional mobility and control were complemented by self-reported embodiment, assessed through a questionnaire targeting agency, ownership, and body representation. ResultsThe neurally-controlled prosthesis enabled intuitive and responsive control. Compared to the subjects prescribed prosthesis, the prosthesis yielded improved temporal gait symmetry during walking (symmetry index: 0.93 vs. 0.59, with 1 indicating perfect stance time symmetry), increased prosthetic-side weight-bearing during sit-to-stand and squatting, and successful execution of a step-over-step stair ascent strategy--an outcome not achievable with the subjects prescribed device. Embodiment scores were consistently higher with the neurally-controlled prosthesis compared to the prescribed device across multiple domains, including agency, ownership and body representation. ConclusionsThis study is the first to directly compare a prescribed microprocessor knee with a bone-anchored, neurally-controlled powered prosthesis. By combining osseointegration, surgically reconstructed agonist-antagonist muscle pairs, and powered actuation, the system improved gait symmetry, greater prosthetic-side loading, and step-over-step stair ascent. These results demonstrate the novelty and promise of integrating surgical and mechatronic innovations to restore both functional mobility and embodied control after transfemoral amputation. Trial registrationThis study was approved by the Institutional Review Board at MIT (Protocol No. 2503001589).

PurposeTo evaluate the feasibility, impacts, and perspectives of a family-led robotic walking intervention. Materials & MethodsThis single-arm interventional study recruited participants aged [&ge;]4 years with pediatric-onset neuromotor disorders. Participants were lent a robotic walker and recommended to use at least 150min/week for 12-weeks. Robotic walking use, acceptability, practicality and adverse events were tracked. Family goals were measured before and after training period using Canadian Occupational Performance Measure (COPM). Quality of life was examined using EQ-5D-Y, Carer-QoL, and CP-CHILD. Quantitative data were analyzed using descriptive statistics (median (25th-75th percentile)) and Wilcoxon signed-rank tests. Qualitative interviews captured family perspectives and were analyzed using thematic analysis. Results15 participants aged 4-23 completed this study. Participants trained 5 (3.5-6) times for 150(82-181) minutes and took 7,544(4,640 - 9,575) steps each week. Adverse events occurred in <1% (16 minor, 1 moderate) of robotic walking sessions. Performance (3.5 (1.9-4.5), p=<0.001) and satisfaction (3.3(3.0-5.0), p=<0.001) of goals increased. Parents described positive changes in social experiences and family interactions and difficulties with the logistics of robotic walking. ConclusionsThis family-led robotic walking intervention resulted in improvements in individual goals, though families did struggle with some logistics of robotic walking, such as; transport and difficulties with the device.

Individuals with post-stroke aphasia live with long-term disabilities, yet they do not know whether they will improve their communication and cognitive skills over time. We propose a "Therapy Calculator" to provide patients with a better understanding of likely recovery as they engage with therapy. Using a large dataset of rehabilitation outcomes from a digital therapeutic called Constant Therapy (3.5 million therapy sessions of 18,000+ users), we developed a machine learning algorithm that estimates the probability of improvement from one functional landmark (i.e., a given skill level) to the next in a functional domain (e.g., reading) while accounting for age, etiology, starting performance, and frequency and duration of therapy. This logistic regression model performed a binary classification task, i.e., whether patients can improve to the next landmark, with an average F1 score of all models at 0.84, suggesting reliable prediction of moving to the next landmark. Then, we created an online "Therapy Calculator" to assess a new users current functional level and demographic information, and make predictions by passing these features into models trained on relevant subsets of historical data. The findings indicate that our model can provide reliable predictions for patients beginning self-managed SLT, and therapy calculator is publicly available.

BackgroundFreezing of gait (FOG) affects up to 80% of people with advanced Parkinsons disease and is difficult to elicit reliably during clinical assessments. Augmented reality (AR) offers potential for standardized FOG provocation by presenting virtual triggers in any environment. ObjectiveTo evaluate whether an AR-based turning task could elicit FOG in a graded, dose-dependent manner and assess user experience with the technology. MethodsThirteen people with Parkinsons disease (8 freezers, 5 non-freezers) completed an AR pillar-turning protocol across two cohorts: clinic-based (n=4, all freezers) and laboratory-based (n=9, mixed). Participants performed 360{degrees} turns around a virtual pillar presented at three diameters (0.6, 0.4, 0.2 m) using a Microsoft HoloLens 2, manipulating turning radius to vary task difficulty. FOG episodes were video-recorded and independently annotated. Participants completed perception questionnaires and the New Freezing of Gait Questionnaire (NFOG-Q). ResultsAll clinic freezers exhibited FOG during AR pillar turns, with a clear dose-response relationship: mean episodes increased from 2.3 at 0.6 m to 5.3 at 0.4 m to 8.5 at 0.2 m diameter. No laboratory participants experienced FOG during pillar turns, though one lab freezer froze during return turns. NFOG-Q profiles indicated comparable daily-life FOG severity between clinic and laboratory freezers, suggesting environmental factors drove differential outcomes. Participants reported positive experiences with AR quality, safety, naturalness of movement, and rapid adaptation, though clinic participants reported higher immersion than laboratory participants. ConclusionsAR-based pillar-turning successfully elicited graded FOG in susceptible individuals within a FOG-provoking environment, demonstrating proof-of-concept for scalable virtual trigger paradigms. Effectiveness depends on matching environmental context to individual FOG susceptibility, with implications for standardized clinical FOG assessment.

Sound- and music-based gait training (SM-GT), including rhythmic auditory stimulation and music-based movement approaches, has been shown to improve gait and functional outcomes in people with Parkinsons disease (PD). However, little is known about how such interventions are recognized and implemented in real-world settings. This study investigated awareness and actual use of SM-GT among people with PD in Japan across inpatient rehabilitation, home-based rehabilitation, and daily-life contexts. A cross-sectional questionnaire survey was conducted among 62 people with PD recruited from public lectures and exercise programs. Participants reported their awareness of SM-GT, experiences of use in different contexts, types of auditory cues employed, and functional status including activities of daily living, gait and balance, and freezing of gait. Overall, 57.4% of participants reported being aware of SM-GT, whereas actual use remained limited across contexts (26.1% in inpatient rehabilitation, 9.1% in home-based rehabilitation, and 31.1% in daily-life contexts). Awareness was higher among participants with inpatient rehabilitation experience than among those with home-based rehabilitation experience; however a substantial gap between awareness and actual use was observed across all settings. While metronomes were the most frequently recognized auditory cue, hand clapping or verbal cueing and music were more commonly used in practice. Awareness and use of SM-GT also varied according to functional status, with relatively higher implementation among individuals with mild functional impairment. These findings reveal a pronounced discrepancy between recognition and real-world implementation of SM-GT in Japan, highlighting the need for strategies that facilitate translation of evidence-based auditory interventions into routine rehabilitation and everyday walking for people with PD.

BackgroundChildren with unilateral spastic cerebral palsy (USCP) often rely on trunk compensation due to impaired upper limb control, but current clinical tools do not directly capture trunk involvement. Marker-based systems are challenging to use with children, while computer vision methods like OpenPose offer a promising, scalable alternative for kinematic analysis but need to be validated. PurposeWe validated OpenPose for quantifying trunk recruitment during bimanual play in children with USCP and examined how the interventions Constraint-Induced Movement Therapy (CIMT) and Hand-Arm Bimanual Intensive Therapy (HABIT) influence trunk use. MethodsWe analyzed videos of children with USCP who underwent CIMT or HABIT. OpenPose was used to extract trunk displacement angle (TDA) and trunk rotation angle (TRA), which were compared to hand function scores. OpenPose was validated against a 3D motion analysis system in typically developing adults. Reach-phase kinematic variables were also assessed. ResultsOpenPose showed high validity for TDA and lower validity for multi-planar TRA. TDA and TRA did not correlate with baseline hand function. HABIT reduced TDA, while CIMT slightly increased it. No significant changes were found in velocity, movement time, or variability. ConclusionsOpenPose is a viable tool for capturing gross trunk motion. Trunk recruitment patterns differed by intervention, supporting the need for personalized approaches.

PurposeRobotic walkers are a new and novel technology with growing evidence of benefits for children living with mobility impairments. However, little is known about how using these devices at home impacts families. This study aims to explore parents perceptions of home-based robotic walking and the impacts on their family and their child living with a mobility impairment. Materials and MethodsQualitative interviews were conducted with seven parents who have a child who used a robotic walker in their home for at least six months. Thematic analysis was used to analyze all interviews. Themes were then mapped to the F-words for child development. ResultsUsing a robotic walker at home led to family bonding and created new ways for parents and siblings to interact with the child living with a mobility impairment. Many children enjoyed using the robotic walker. This, combined with being able to direct its use in their own environments, contributed to less parental stress than was associated with other rehabilitation interventions. However, some parents discussed an increase in parental stress due to certain logistical aspects, getting their child in and out and transporting the robotic walker. Finally, parents discussed that obtaining the device was a financial burden for them. ConclusionRobotic walking in the home environment impacts family relationships and parental stress. Understanding families experiences can inform decision-making by families and practitioners around the appropriateness of robotic walker use for a child living with a disability.

IntroductionTraditional clinical motor function assessment scales, despite their importance, often fail to identify the underlying neurophysiological mechanisms of postural control disorders. In this regard, stabilography, as an objective quantitative method, acquires particular diagnostic value. The aim of this study was to identify and compare frequency markers of postural control disorders in adults with cerebral palsy (CP) and healthy subjects using stabilographic signal power analysis in narrow frequency ranges. MethodsStabilograms were recorded while performing a visual feedback task and its combination with additional cognitive loads in two groups: adults with CP (n=8) and a control group (n=8). For the analysis, the stabilographic signal power was calculated in ten narrow frequency ranges (0.05-12.0 Hz). ResultsBased on the analysis of the stabilographic signal power, individual postural control profiles were identified, defined by three key patterns: <<hyperactivation>>, <<exhaustion>>, and <<optimization>>. The obtained data were interpreted within the framework of N.A. Bernsteins level theory of movement construction, where the identified patterns reflect an imbalance or synergy of various postural regulation circuits--from subspinal to corticocerebellar. ConclusionsThe proposed method for analyzing stabilogram power enables the identification of individual neurophysiological profiles of postural control disorders. The identified <<optimization>> marker indicates preserved neuroplastic potential. The results of the work open the way to a well-founded personalized rehabilitation, the strategy of which consists of transforming a pathological pattern (<<hyperactivation>>, <<exhaustion>>) into an optimal one (<<normalization>>) through targeted modulating effects on specific levels of movement construction.

Centre of mass (COM) is a key measurement used to assess balance and mobility. Marker-based motion capture systems have traditionally been used to measure COM, but they are time-consuming and prone to marker error. Markerless motion capture systems offer a potential alternative, reducing setup time while maintaining accuracy. The ease of collecting markerless data may be particularly beneficial when study participants have limited mobility, such as those with stroke. This study aimed to determine the differences in COM measurements between marker-based and markerless motion capture systems during balance and mobility tasks in individuals with sub-acute stroke. Seventeen participants completed the following tasks: walking, quiet standing, sit-to-stand, rise on toes, and backward reactive stepping. COM data were analyzed using two markerless models, a default with 17 segments and a fit model with 11 segments to match the marker-based model to be compared as the reference. The results showed high correlations (R2 = 0.75 to 0.999) and low root-mean-square differences (< 2 cm) in the anterior-posterior and medial-lateral directions. Larger differences (> 4 cm) were observed in the superior-inferior direction, particularly with the default model. These findings suggest that markerless motion capture can be used to measure COM in people with stroke, and that model selection plays an important role in COM estimates.

BackgroundMarkerless motion analysis using deep learning is attracting attention in the field of rehabilitation; however, the three-dimensional measurement accuracy in finger joints, which are prone to self-occlusion, has not been sufficiently validated. This study aimed to validate the accuracy of finger joint angle measurements obtained using a marker-less system based on DeepLabCut (DLC) and Anipose by comparing it with the clinical standard of goniometric measurements. MethodsForty-one healthy adults were recruited. Videos from ten participants were used for DLC training, whereas the remaining 31 served as the analysis subjects. Eight flexion movements (wrist, thumb, index, and middle finger) were recorded using five synchronized cameras. The DLC tracked 2D keypoints, and Anipose performed 3D reconstruction to calculate the angles. Goniometric measurements were performed simultaneously for comparison. The agreement between methods was evaluated using Bland-Altman analysis to identify fixed and proportional biases. FindingsHigh agreement was observed between the angles estimated by marker-less analysis and goniometer measurements, and most data points were within the 95% limits of agreement. However, a significant proportional bias, where the error increased with an increase in flexion angle, was observed in distal joints, such as the thumb interphalangeal joint and index/middle proximal interphalangeal joints. InterpretationThis system demonstrated clinically acceptable validity for measuring finger range of motion. However, underestimation is likely to occur in the distal finger joints and at maximal flexion owing to the influence of occlusion, necessitating consideration of proportional bias. This method represents a noninvasive, low-cost tool for assessing hand function.

ObjectiveAccurate stride length measurement is essential for assessing functional mobility, yet gold-standard methods remain confined to laboratory settings. This study aimed to develop and validate a computationally efficient, interpretable linear model for predicting stride length using thigh- and shank-mounted inertial measurement units integrated into a wearable neuromodulation sleeve. MethodsData from the sleeve were collected from 29 healthy adults performing walking bouts at four self-selected speeds. Participants traversed a pressure-sensitive gait mat, providing gold standard labels. A linear regression model was developed from engineered features from the kinematics data streams and validated against a held-out test set (n = 6) using leaveone-participant-out cross-validation. ResultsThe final linear model utilized five predictors: participant height, shank range of motion (ROM), thigh ROM, and thigh swing duration metrics. It achieved high predictive accuracy with a mean absolute error (MAE) of 5.98 cm, a mean absolute percentage error (MAPE) of 4.53%, and an R2 of 0.89. The model significantly outperformed naive baseline models (p < 0.05) and performed similarly to more complex non-linear architectures, such as neural networks and random forests. Notably, 88.4% of strides were predicted within 10% of the ground truth. ConclusionA parsimonious linear model leveraging proximal limb kinematics provides accurate and biomechanically interpretable stride length estimation. Low computational demand makes it suitable for real-time, ondevice gait monitoring in wearable assistive technologies, facilitating clinical assessments in real-world environments.

ObjectiveTo describe the design and development of NeuroRehab VR, a fully immersive, specific and gamified virtual reality (VR) software aimed at improving the quality of life and reducing disability in post-stroke patients. MethodsA public-private collaborative research project was carried out between 2022 and 2024 by a multidisciplinary and multicenter team comprising neurologists, rehabilitation specialists, physiotherapists, exercise and sport sciences professionals and members of the company Dynamics VR Rehab, including engineers, developers, computer programmers, game designers, and digital artists. The project was structured into three phases: preproduction, production, and postproduction, with periodic focus group meetings and testing sessions with patients in the subacute phase of stroke held every one to two months. ResultsIn the Preproduction phase, the multidisciplinary team discussed the initial concepts and, using the SCRUM methodology together with feedback from pilot patients, developed the software design. In this process, three thematic environments (i.e., home, nature, and science fiction) were established, along with five activity types targeting upper limb rehabilitation: fine motor skills, gross motor skills, balance, rhythmic movements, and movement speed. The software incorporated fully immersive VR, advanced hand tracking technology, and adaptive gamification elements. During the Production phase, these components were implemented and consolidated into a functional prototype. Finally, in the post-production phase, several adjustments were made after identifying minor issues, with the aim of improving activity responsiveness and refining the user experience for both patients and clinicians. ConclusionNeuroRehab VR represents a promising tool to be integrated into post-stroke rehabilitation programs and is being tested though a clinical trial. Moreover, this public-private, multidisciplinary, and multicenter collaboration model constitutes an effective framework for the design and development of technologically driven solutions applicable to clinical rehabilitation settings.

Pusher syndrome is a disorder of postural control, characterized by an altered perception of upright body orientation. While visual verticality perception remains intact, patients incorrectly perceive their tilted body posture as upright, resulting in active resistance to posture correction. This perceptual mismatch offers a potential target for therapeutic interventions. We evaluated a newly developed Tilted Reality Device (TRD) designed to recalibrate body verticality perception by subtly tilting the patients real-time visual environment towards the ipsilesional side in a series of four patients with pusher syndrome. We implemented a three-phase experimental design: pre-manipulation (normal view), manipulation (TRD tilted 20{degrees} ipsilesionally), and post-manipulation (normal view). Passive body tilts were performed while we recorded body orientation. Fifteen healthy older adults served as controls. The behavioral changes were assessed via tilt angle analysis and were statistically compared using Crawford-Garthwaite Bayesian methods. Two of the four patients showed reduced resistance to ipsilesional body tilts during the TRD manipulation. Two patients also demonstrated an aftereffect. Our findings only partly confirmed our expectations; possible limitations are discussed. Further research is needed to evaluate our TRD in its potential treatment effects in pusher syndrome and better understand the mechanisms involved in the recalibration of upright body orientation perception in patients with pusher syndrome.

BackgroundDespite recommendations in clinical guidelines, clinical experience indicates that engagement with splints and orthotics varies amongst people after stroke. ObjectivesThe aim of the study was to understand the factors that influence engagement with splints and orthotics in people after stroke. MethodsPeople after stroke who had been wearing a splint or orthotic (also known as devices) for at least 2 months under the care of one Community Neurosciences Team in the UKs National Health Service were included. Semi structured interviews based on the constructs of Banduras Social Cognitive Theory (SCT) were used to gather participants views, and a framework analysis applying the constructs of SCT was completed using NVIVO software. ResultsFour key themes were identified: 1. Self-Regulation; difficulties applying the device and aesthetic acceptability. 2. Self-Efficacy; increased confidence when wearing the device and reduced motivation to wear the device. 3. Outcomes Expectation; reduced falls risk, improved gait, improved balance, maintaining range of movement, and negative effects such as discomfort, pain, itching. 4. Social Support; support needed to apply the device and the burden on family members/carers to apply the device correctly. ConclusionsThe findings of this study highlight key factors that influence engagement with orthotics and splints. These include difficulty applying the device after stroke, device aesthetics, comfort, and the importance of continued support from carers. Manufacturers should consider how people after stroke can independently don and doff devices. Education of carers and family members also appears key to support their engagement.

BackgroundIndividuals with severe mobility impairments (SMI) often experience significant psychological distress and chronic pain. Virtual walking (VW) presents an innovative rehabilitation approach to improve mood and alleviate pain. This study aimed to develop a home-based VW system with integrated mood and symptom tracking and to report on its feasibility and usability in a user study with individuals with SMI. MethodsA multidisciplinary, iterative frame-work guided the systems development. Following initial contextual research and design iterations, a user study was conducted with 11 participants with SMI. A repeated measures pre-post design was employed. Feasibility and usability were primarily assessed through post-study qualitative interviews, analyzed via content analysis. Changes in mood and symptoms were measured immediately before and after each session. Momentary mood was captured using an in-virtual reality (in-VR) two-dimensional (2D) affect grid, while embedded single-item state ratings were used to track anxiety, depressed mood, and pain. Daily mood changes and symptom trajectories were analyzed using logistic regression and generalized estimating equations (GEE), respectively. ResultsContextual research guided the system design towards enhancing accessibility, ergonomics, and therapeutic engagement. The final VW system featured three core modules: locomotion, multi-sensory feedback, and mood/symptom tracking. Qualitative analysis of the user study revealed high acceptance for the VW system, alongside challenges related to content variety and hardware ergonomics. Each intervention session was significantly associated with an immediate positive mood shift (odds ratio (OR) = 1.83), as measured by the affect grid. Furthermore, GEE models revealed a significant reduction in self-reported depression and anxiety symptoms over the intervention period (all P < 0.01). ConclusionsThis study confirms the feasibility and acceptability of the novel VW system for home-based use by individuals with SMI. The preliminary evidence suggests the system has high potential as a tool for improving mood and alleviating psychological distress. Future large-scale randomized controlled trials are warranted to establish its clinical efficacy. Trial registration numberNCT07073144-07/17/2025.

BackgroundThree-dimensional gait analysis (3DGA) is widely used to support clinical decision-making in individuals with motor impairments. However, kinematic outputs depend strongly on the underlying biomechanical model. The open-source Conventional Gait Model II (CGM2) integrates updates to joint centre estimation (CGM2.1), inverse kinematics (CGM2.2), and cluster-based segment tracking (CGM2.3). While previous work demonstrated consistency among CGM2 variants in typically developing children, their effect in clinical populations remains unknown. This study quantified how CGM2 variants influence gait kinematics in individuals with cerebral palsy (CP). MethodsTwenty-one individuals with CP (GMFCS I-II) underwent 3DGA using a 12-camera motion capture system and a CGM2.3 marker set. Hip, knee, and ankle kinematics from 487 gait cycles were computed using pyCGM2. Differences between CGM2.1, CGM2.2, and CGM2.3 were evaluated using Mean Absolute Deviation (MAD) and the adjusted coefficient of determination (R2). ResultsOverall, small differences were observed between model variants. MAD values were typically below 5{degrees} for most joints and planes, with high correlation between curves (R2>0.7). Hip rotation showed the largest discrepancies, with maximum MAD up to 7.7{degrees} when comparing CGM2.2 and CGM2.3. Differences between CGM2.1 and CGM2.3 were greater in the transverse and frontal planes but remained within acceptable limits (<5{degrees}), except for hip rotation. ConclusionThe CGM2 variant selection has limited impact on gait kinematics in individuals with CP, and most differences fall within known repeatability error. However, transverse-plane kinematics, particularly hip rotation, should be interpreted with caution when comparing data across CGM2 variants.