Gait & Posture

Low cost inside out wearable trackers can be deployed at scale to measure body motion, but errors in estimated sensor position propagate through coordinate transformations into derived gait and dynamic-stability metrics. Healthy adults walked on a treadmill at 0.5 to 2.0 m/s while VIVE Ultimate Tracker (VUT) and Vicon data were recorded. Data-driven calibration models were developed to correct tracker coordinates and to estimate full body centre of mass (CoM) from a sacrum-only configuration. Agreement with Vicon was assessed using RMSE, mixed-effects Bland-Altman limits of agreement, MAE, and intraclass correlation coefficients. Calibration improved coordinate-level agreement. For gait parameters, model-corrected VUT showed small errors against Vicon (MAE: 0.24 to 0.71 mm step height, 1.73 to 4.63 mm step length, 0.15 to 0.95 mm step width, 0.26 to 0.88 mm foot clearance). Proxy CoM-derived margin of stability (MoS) agreed excellently with Vicon. For the sacrum-only pipeline, calibration reduced CoM RMSE from 103.65 to 104.04 mm to 7.55 to 8.95 mm, and markedly reduced systematic error in stability outcomes, with extrapolated CoM bias decreasing from 172.92 to 0.29 mm and MoS bias from -75.09 to -3.54 mm. Data-driven calibration improved the measurement utility of low-cost VUTs, enabling inexpensive, relatively simple gait and stability measurement from a sacrum-only setup in controlled settings.

Purpose: Treadmills (TM) are widely used for gait assessment in older adults (OA), yet their ecological validity across inclined terrain remains underexplored. This study compared spatiotemporal, physiological, and kinetic gait outcomes between TM and overground (OG) walking across flat, uphill, and downhill terrain in OA and younger adults (YA), and examined sensorimotor predictors of speed discrepancies. Methods: Twenty-six OA (70{+/-}6 years; 22 women) and 24 YA (26{+/-}5 years; 7 women), none with prior TM experience, completed matched TM and OG trials across three terrain conditions. Self-selected TM speed was determined using a bidirectional protocol. The modified Clinical Test of Sensory Interaction in Balance quantified sensorimotor profiles. Mixed-design ANCOVAs and multiple regression examined condition, inclination, and group effects with sex as a covariate. Results: TM speeds were consistently slower than OG across all conditions in both groups ({Delta} = -0.35 m/s, d = -1.67), with shorter stride length, lower cadence, and altered support phase timing; YA showed larger reductions and a greater shift toward double support than OA. Foot clearance at midswing was largely preserved across modalities. TM walking elicited higher heart rate and RPE despite slower speeds, most pronounced in OA uphill. Ground reaction forces and loading rates were substantially reduced on the TM. Sensorimotor profiles predicted the downhill speed discrepancy (R2 = 0.49), with vestibular and somatosensory contributions as independent predictors alongside age group. Conclusion: TM-derived speed, spatiotemporal, and physiological measures are not interchangeable with real-world ambulation data in OA across inclined terrain.

Introduction: Stair walking challenges balance and coordination in older people. Bench-stepping training improves stair climbing speed in healthy older women. This study assessed whether bench-stepping also improves dynamic balance and movement complexity during stair walking. Methods: Stair walking data were obtained from a previous study involving 45 healthy older women (69y+/-4) that assessed the effects of a 12-week bench-stepping intervention with non-training controls. Centre-of-mass acceleration was measured during stair ascent and descent. Linear dynamics included time, acceleration magnitude, and harmonic ratios (HR; indicating symmetry). Movement complexity was quantified using nonlinear dynamics including sample entropy (SE), recurrence quantification analysis (RQA), and fractal dimension (FD). Results: For stair ascent, increased speed (p =0.018, R2partial =0.093,) was accompanied by proportional increases in acceleration magnitudes (p=<0.039, R2partial =0.078-0.101). SE decreased more in the intervention group (p=<0.012, R2partial =0.049-0.101), indicating more predictable dynamics. In contrast, for stair descent, no changes in speed or acceleration magnitudes were observed. However, SE (p =0.001, R2partial =0.082) and maximum RQA line length (p= 0.008, R2partial =0.057) of vertical acceleration increased significantly compared to controls, indicating lower predictability and more persistent recurring patterns. No significant changes were found for other outcomes. Exploratory factor analysis revealed distinct differences in motor behaviour between stair ascent and descent. Conclusion: Bench-stepping training induced measurable changes in stair walking dynamics. Specifically, sample entropy shows potential as a sensitive marker of altered motor complexity, particularly of vertical accelerations. Interestingly, the direction of changes in unpredictability differed between stair ascent and descent, suggesting different underlying control strategies.

BackgroundBalance maintenance in humans is not only a mechanical process, but it also relies on continuous interactions between cortical activity and body dynamics. Alterations in postural sway are commonly observed in aging and stroke and are frequently used to assess balance impairment. However, similar balance deficits do not necessarily reflect similar underlying sensorimotor control mechanisms. Therefore, investigating brain-body interactions and their relationship to characteristics of postural behavior may provide deeper insights into the neural processes underlying balance dysfunction in these populations. ObjectiveTo determine whether brain-body coupling is associated with characteristics of postural behavior captured by the temporal organization of postural fluctuations beyond conventional magnitude-based measures of postural sway, and whether these relationships differ between stroke survivors, healthy older adults, and young adults. MethodsEEG and center-of-pressure (CoP) signals were recorded simultaneously in stroke survivors (n = 12), healthy older adults (n = 18), and young controls (n = 17) during quiet standing under 4 different manipulated sensory conditions. Sway-based corticokinematic coherence (CKC) as well as linear and nonlinear features (sample entropy, SE; fractal dimension, FD) of CoP were extracted. Linear mixed-effects model assessed associations between features and CKC, and model performance was compared using Akaike Information Criterion. Multidimensional state vectors were constructed from CKC, linear and nonlinear CoP features, and Euclidean distances between consecutive states in the standardized feature space were computed to quantify condition-dependent transitions in brain-body control organization. ResultsNonlinear features showed significant, group- and feature-dependent associations with CKC in the mediolateral direction, driven by significant SE and FD effects in the stroke group and an SE effect in the older group, while no significant associations were observed in the young group. Including nonlinear features in baseline models containing only linear CoP features significantly improved model fit. CKC alone showed low classification performance (AUC 50 to 65), whereas combining CKC with linear and nonlinear features improved group discrimination (AUC up to 0.86). State-space transition analysis revealed larger condition-dependent transitions in stroke participants compared with healthy older adults, particularly going from eyes open to eyes closed when standing on foam. ConclusionBrain-body coupling during standing may be understood more comprehensively by factoring in the temporal structure of fluctuations rather than their amplitude alone. These findings support the use of nonlinear dynamical features, combined with CKC, as potential markers of balance impairment.

Impaired gait performance and stability is a key symptom often defining disease outcome in people with Multiple Sclerosis. Step-by-step foot placement control in response to variations in the center-of-mass kinematic state is a crucial gait stability mechanism, especially in the mediolateral direction. Even though it is known that people with Multiple Sclerosis are at an increased risk of falling, step-by-step foot placement control remains to be characterized in this population. Here, we explored characteristic foot placement control in ten people with early stage Multiple Sclerosis, compared to 21 controls walking at a similar average gait speed, during 1-minute steady-state treadmill walking. Kinematic data were analyzed using a linear feedback model that correlated foot placement with the center-of-mass kinematic state during the preceding swing phase. People with Multiple Sclerosis demonstrated step-by-step foot placement control in both the mediolateral and anteroposterior directions. No differences were found in foot placement precision between groups. However, foot placement responses to variations in center-of-mass velocity proved stronger in people with Multiple Sclerosis. Moreover, the contribution of mediolateral center-of-mass velocity feedback to the control mechanism was higher in people with Multiple Sclerosis as compared to neurologically healthy controls. Our results suggest that foot placement control is still retained in early clinically evident stages of Multiple Sclerosis, but is realized through differently weighted sensory feedback control.

Impaired motor control post-stroke results in reduced walking speeds and increased gait variability. This variability reduces reliability and makes identifying longitudinal changes via gait analysis difficult since changes may occur within the margin of measurement error. We quantified intra-class correlation coefficients (ICC) and minimal detectable change (MDC) in post-stroke individuals and neurotypical individuals walking at matched speeds, to isolate the impact of gait speed and post-stroke impairments on gait-analysis reliability. We collected gait data over two days from N=15 post-stroke individuals walking on a treadmill at their self-selected speed, and from N=13 age- and sex-matched neurotypical controls walking at both their self-selected speed and a speed matched to a post-stroke participant. We calculated ICC and MDC values for spatiotemporal variables, bilateral joint ranges of motion (ROM), and bilateral peak propulsive and peak vertical ground reaction forces (GRF). Spatiotemporal ICCs showed excellent reliability across groups (range [0.813-0.988]), yet MDC values were greater post-stroke than in speed-matched controls. ICCs for joint ROM ranged from poor to excellent reliability across groups ([0.362-0.960]). Post-stroke joint ROM MDCs were 27%-53% of the gait ROM compared to 11%-42% in neurotypical controls. ROM MDCs were greater in the non-paretic compared to the paretic extremity. ICC for peak GRFs showed good to excellent reliability across groups (range [0.778-0.980]), with post-stroke peak GRF MDCs greater than in speed-matched controls. Our results suggest that stroke related neuromotor impairments influence reliability beyond the effects of walking speed alone, and we provide quantitative MDC benchmarks for interpreting gait changes post stroke following clinical interventions.

Static force plates (FP) are the gold standard for measuring ground reaction forces (GRF) and computing joint moments through inverse dynamics in gait analysis. However, they are restricted to controlled environments, and the number of steps analyzed is limited by the plates embedded in the floor. To address these limitations, portable solutions such as sensorized insoles, socks, or shoes have emerged. Yet, creating wearable systems capable of measuring three-dimensional GRF in real-world conditions remains challenging. Current sensorized shoes often incorporate thick sensors (up to 2 cm), reducing usability and limiting their application in pathological populations or dynamic tasks like running. This study evaluates the usability of ShokacShoes, a novel sensorized shoe integrating three thin, three-dimensional force sensors, and explores its potential as a Wearable Force Plate (WFP). Eight healthy participants performed slow, natural, and fast walking using two insole configurations. Force and temporal metrics were derived from WFP and FP data. Results indicate that WFP enables accurate step segmentation and detects significant effects of speed and insole type on temporal and force metrics, confirming its reliability under different walking conditions. Comparisons with FP revealed differences in force metrics and signal morphology, though temporal parameters remained consistent. These results are likely due to sensor quantity and positioning. Thereby, ShokacShoes represent a valid solution capable of measuring three-dimensional forces within commercial footwear. Future work will focus on validating the applicability of a new version of ShokacShoes against gold-standard FP in a comprehensive validation study involving diverse real-world scenarios and pathological conditions.

Age-related decline in postural control is an important factor that increases the fall risk of older adults. Fingertip vibrotactile stimulation has been developed to provide light touch-like somatosensory input. However, evidence regarding differences among older age groups is limited. This study examined the effects of fingertip vibrotactile stimulation on postural control in 348 community-dwelling older adults classified as young-old (age 65-74 years), old-old (age 75-84 years), and oldest-old (age 85 years or older). Participants stood with eyes closed and feet together under stimulation and no stimulation conditions. The center of pressure (COP) velocity and COP area were measured using a force plate. The natural log-transformed COP area was used for the analysis. Linear mixed models were used to examine the effects of age group, stimulation conditions, and measurement segments. The COP velocity under the stimulation condition was significantly lower than that under the no stimulation condition; however, the COP area did not change significantly. Significant main effects of age group were observed for both COP indices, but no interaction between age group and stimulation condition was observed. Fingertip vibrotactile stimulation may reduce the COP velocity across older age groups, thus reflecting the effects on postural adjustment frequency.

Older adults sustain disproportionately severe injuries from trip-induced falls during obstacle crossing. Such falls depend partly on forward momentum when the foot crosses the obstacle. MOSAP, an index of passive dynamic gait stability, reflects this momentum. We quantified MOSAP and a synergy index from uncontrolled manifold analysis of step length and extrapolated center of mass in 25 young (21.6 {+/-} 3.5 yr) and 23 older adults (68 {+/-} 4.3 yr) during unobstructed and obstructed walking, to test whether MOSAP increases during obstacle crossing and whether it is actively stabilized at each step. Both groups increased MOSAP progressively over two approach steps by reducing forward momentum and shifting the center of mass posteriorly. Older adults showed greater increases at the crossing steps. The synergy index was positive for all steps, showing that deviations in step length and extrapolated center of mass covaried to stabilize MOSAP at step-specific values. The synergy index was not influenced by age. We conclude that adults actively recruit passive body mechanics while approaching and crossing obstacles to reduce the risk of a trip becoming a fall. Older adults amplify this strategy to compensate for diminished neuromuscular corrective capabilities.

BackgroundThe use of specialized perturbation systems has become an increasingly popular approach for investigating walking stability. By accelerating or decelerating one belt, researchers can induce slip- and trip-like perturbations in a controlled laboratory setting. However, many existing studies rely on specialized perturbation systems that require expertise in device-specific software and handling of the equipment, limiting the accessibility of perturbation-based gait research to laboratories with access to such equipment. To address this limitation, we developed an open-source method capable of inducing slip- and trip-like perturbations using a standard split-belt treadmill. Here, we 1) describe the hardware and software components of the system, 2) validate the applications accuracy and precision, and 3) characterize the stability demands imparted by the perturbations with spatial stability measurements. Measured perturbation onset delay and duration were compared to the desired onset timing and programmed duration in addition to step length, step width, minimum mediolateral margin of stability, and sagittal-plane whole-body angular momentum range during the perturbed and recovery steps. ResultsFive participants with traumatic unilateral transtibial limb loss experienced perturbations consisting of brief, rapid increases or decreases in unilateral treadmill velocity, eliciting a "slip" or "trip". The mean (standard deviation) onset delay was 183.3 (9.7) ms, or 24.18% (1.91%) of stance duration. Mean perturbation duration was 239.90 (7.5) ms, 18.14% longer than the intended duration. The perturbations produced measurable changes in gait stability, such as increased step length during the perturbed step and step width during the subsequent recovery step in addition to increased minimum mediolateral margin of stability and sagittal whole body angular momentum. ConclusionThis open-source method successfully induced instability in individuals with impaired balance, demonstrating its feasibility as an accessible alternative to specialized perturbation systems. Future work will focus on refining both the software and hardware components to further improve timing, accuracy, and consistency.

Objective: To investigate the clinical validity of finger-worn accelerometers for providing a comprehensive assessment of upper-limb motor performance in stroke survivors in real-world environments, compared to wrist-worn accelerometers, and to examine how the clinimetric properties of wearable-based motor performance measures vary with the duration of patient data collection. Design: Cross-sectional observational design. Setting: Research laboratory and free-living environments. Participants: Twenty-seven stroke survivors aged 18-80 years with ischemic or hemorrhagic stroke at least six months prior to enrollment and mild-to-moderate upper-limb impairment without severe range-of-motion restrictions were enrolled. Three participants were ineligible and four withdrew, resulting in a final cohort of 20 participants (N = 20). Interventions: Not applicable. Main Outcome Measures: Wearable-based motor performance measures derived from fine-hand movements, gross-arm movements, and the combination of fine-hand and gross-arm movements captured by finger-worn and wrist-worn accelerometers in naturalistic settings for 6.4 {+/-} 1.8 days. Results: Wearable-based motor performance measures from fine-hand movements demonstrated the strongest convergent validity, known-group validity, and test-retest reliability, followed by those from combined and gross-arm movements. Convergent validity and test-retest reliability of wearable-based motor performance measures improved with longer monitoring durations, with four days being sufficient to obtain accurate and reliable upper-limb measures. Conclusions: Wearable-based motor performance measures from finger-worn accelerometers provide a more comprehensive assessment of upper-limb motor performance than those from wrist-worn accelerometers, supporting their use for real-world monitoring in stroke survivors. Furthermore, the improvements in clinimetric properties of wearable-based motor performance measures with longer monitoring durations highlight the importance of multi-day monitoring to mitigate day-to-day variability and ensure robust assessment.

Background: Gait impairment is common among people with multiple sclerosis (PwMS) and is an important marker of disease progression. However, gait assessments typically require in-person evaluations. Objective: To describe the pose-estimation-based method for estimating spatiotemporal gait parameters from a single consumer-grade video, and evaluate the feasibility of home video collection by PwMS. Methods: In a single-center longitudinal digital phenotyping study, ambulatory adults with MS completed a standardized walking task recorded in the frontal plane. Pose estimation (MediaPipe Pose, Ultralytics) and custom scripts were used to estimate gait parameters from videos. Participants were invited to record walking videos at home using personal devices. Adoption and technical feasibility were evaluated across two home video data acquisition phases, with iterative protocol refinements. Results: The in-clinic study included 132 participants; 55 contributed home videos. In Phase I, while home video adoption was low (45% [30/66]), 87% [26/30] uploaded [&ge;]1 video of sufficient quality for gait analysis. After protocol refinements, 100% [25/25] uploaded [&ge;]1 high-quality video. Overall, high-quality frontal-plane videos were obtained at similar rates at home (92% [97/105]) and in-clinic (91% [423/467]). Conclusions: Home walking videos can feasibly be collected by PwMS to estimate gait parameters, providing an accessible approach for remote gait monitoring.

Importance: There are very few interventions designed for individuals with the most severe mobility impairments. Robotic walking may be an effective way to facilitate exercise in this population. Objective: To examine how robot-assisted walkers physical parameters and user characteristics moderate the exercise intensity achieved by individuals with neuromotor disorders causing mobility impairments. Design: A prospective study. Intervention: A single-session intervention involving an overground robot-assisted walker that can be used in an endurance mode requiring no voluntary movement or a strength mode during which voluntary movement could impact the gait pattern. Participants: Individuals with pediatric-onset mobility impairments Main Outcome Measures: Participants were characterized based on their age, sex, diagnosis, and Gilette Functional Assessment Questionnaire (FAQ) levels. Heart rate during the final minute of four 5-minute walking conditions: strength mode at fast speed, strength mode at slow speed, endurance mode at fast speed and endurance mode at slow speed was expressed as a percentage of each participant heart rate reserve (%HRR). Linear mixed-effects models were used to evaluate the impact of speed, device mode and user characteristics on the level of exercise achieved. Results: 29 individuals (aged 2-26 years) with mobility impairments (FAQ levels 1-6) completed this study. Fast speeds were associated with a higher %HRR (beta= 2.11, SE = 1.03, p = 0.044). Participants in FAQ class 1 exhibited significantly higher %HRR compared with those in FAQ classes 2 and 3 (beta=18.6, SE=7.31, p=0.017; beta= 16.9, SE = 8.13, p = 0.047, respectively). No other device or participant characteristics were associated with exercise intensity. Conclusions: To facilitate higher exercise levels, users of robot-assisted walkers can increase their speed. Individuals who cannot take steps due to their neuromotor impairments experience the highest levels of exercise. Relevance: The findings in this study highlight the promise of robot-assisted walkers to improve health, particularly in those who often face the greatest barriers to exercise.

Mild cognitive impairment (MCI) is a clinically important stage preceding Alzheimer's disease and related dementias, in which cognitive and balance functions are commonly evaluated using standard clinical assessments such as the Montreal Cognitive Assessment (MoCA) and Mini-Balance Evaluation Systems Test (Mini-BESTest). These assessments are administered episodically by clinicians and may miss functional changes during everyday movement. Recent studies and prior work in the Charlie and Harriet Shaffer Cognitive Empowerment Program (CEP), a therapeutic environment supporting lifestyle intervention and naturalistic social interaction, suggest that wearable and passive behavioral sensing can monitor movement patterns associated with cognitive and balance function in older adults with MCI. However, it remains unclear whether passive waist-mounted IMU data collected during naturalistic movement and social interaction can quantify clinician-rated cognitive and balance outcomes, particularly at the subdomain level, in an interpretable and demographically fair manner. To address this gap, we analyzed weekly IMU recordings collected over 6 months from 44 older adults with MCI in the CEP and trained tree-based ensemble regression models to estimate MoCA and Mini-BESTest total and subdomain scores, with interpretability and demographic fairness evaluation. Our models achieved RMSEs of 3.677 for MoCA and 3.672 for Mini-BESTest, benchmarked against Minimal Detectable Change and Minimal Clinically Important Difference thresholds. Feature importance analysis showed distinct movement signal properties across assessments, with general movement intensity features most informative for MoCA and temporal gait features led by cadence most informative for Mini-BESTest. Demographic bias analysis identified sex-related model bias, mitigated through post-processing while maintaining performance. This study supports the feasibility of wearable-based estimation of clinical assessment scores in older adults with MCI during naturalistic activity, with comparable performance between sexes after bias mitigation. This advances the validation of passive sensing for home monitoring to support clinical decision-making and personalized interventions.

Introduction: Several gait rehabilitation approaches after stroke rely on explicit feedback to promote task-specific voluntary corrections of walking patterns. While these approaches show effectiveness at a group level, individual responses to voluntary corrections can differ, limiting the benefits and translation of task-specific gait interventions. Our goal is to identify biomechanical, neuromuscular, and cognitive characteristics associated with the ability to perform voluntary corrections of walking using explicit visual feedback in people with chronic stroke. Methods: Twenty-eight individuals with chronic stroke completed a single-session treadmill walking protocol, consisting of baseline walking, a voluntary correction condition guided by real-time visual feedback, and a short retention trial without feedback. Reducing step length asymmetry was used as the target to guide voluntary corrections. Clinical assessments included measures of motor impairment, balance, gait function, cognition, and walking capacity. Muscle coactivation was characterized using dimensionality reduction. Associations of clinical assessments with baseline step length asymmetry and residual error in step length asymmetry during voluntary correction were examined using univariate analyses and multivariate regression with LASSO-based variable selection. Results: Eighteen participants successfully reduced step length asymmetry using visual feedback, while ten participants did not reduce asymmetry. Greater residual asymmetry during voluntary correction was independently associated with greater baseline asymmetry, greater lower extremity motor impairment, reduced balance, and increased paretic muscle coactivation (adjusted R2 = 0.46). Neither the direction of asymmetry nor cognitive outcome measures were associated with the ability to correct asymmetry during walking. Immediate retention after feedback removal was limited, with only 4 participants maintaining improvements. Discussion: The ability to perform voluntary corrections of the walking pattern using voluntary corrections after stroke is constrained by motor impairment, balance function, and muscle coactivation. These findings suggest that explicit, feedback-based gait interventions to guide voluntary corrections may benefit individuals with mild to moderate impairments, while individuals with more severe impairments require alternative strategies to guide corrections of the walking pattern.

BackgroundExplosive force generation during the initial acceleration phase is critical for successful base stealing in baseball. Preparatory balance control preceding movement onset may facilitate this process by constraining horizontal ground reaction force (GRF) toward a task-specific direction. However, its contribution to ballistic sprint initiation remains unclear. Research questionDoes preparatory force constraint influence explosive force generation during base stealing, and when during the preparatory phase is this influence greatest? MethodsFourteen baseball players performed 3-m maximal sprints simulating base stealing under time-constraint (Time) and self-paced (Self) conditions. GRF around movement onset were recorded. Peak rate of force development (peak RFD) was computed from onset to take-off. A 250-ms window before the onset was divided into 50-ms bins, and mean resultant length (Rlen), which represents the extent of force constraint, of each bin was calculated. Using statistics analyses, Differences between conditions were tested, and the relationship between the interaction (Rlen x condition) and peak RFD was assessed. ResultsThe peak RFD was greater under the Self condition than under the Time condition, accompanied by a larger Rlen. Furthermore, Results indicated that the force constraint in the 150-100 ms interval preceding the movement onset most strongly influenced the peak RFD. SignificanceThese findings demonstrate that temporally organized preparatory force constraint plays a critical role in explosive sprint initiation during base stealing. Identifying the specific preparatory timing linked to superior force production provides novel mechanistic insight into preparatory balance control and may inform targeted training strategies for ballistic athletic movements.

Background: Prolonging ambulation is an important treatment goal in children with Duchenne muscular dystrophy (DMD). Clinical management targets 'actionable' (i.e., modifiable) impairments, such as progressive muscle weakness and contractures, that underlie gait pathology. Gait classification may improve clinical decision-making, but the utility of gait classification in clinical practice depends on understanding how underlying, actionable impairments contribute to distinct gait patterns, which remains insufficiently understood. The research questions were: (1) Can DMD gait patterns be accurately classified from actionable impairments? and (2) Can the model's predictions be explained, and do these explanations provide clinical utility and increase trust in the model? Methods: A retrospective dataset of 274 lower-limb observations from 137 assessments in 30 boys with DMD was analyzed, including 3D gait analysis, instrumented strength assessment, and clinical examination (manual muscle testing, goniometry and clinical stiffness scale). Observations were classified into the mildly affected, tiptoeing, or flexion gait pattern. Ten predictors representing actionable impairments were included: nine predictors related to muscle weakness and contractures, and body mass index (BMI). A balanced random forest classifier was evaluated with leave-one-group-out cross-validation. Model interpretability was explored using SHapley Additive exPlanations to generate global and local explanations. An interview with a clinical expert assessed the utility of the explanations as the primary outcome, with trust in and expectations of both the model and the explanations as secondary outcomes. Results: The model achieved an accuracy of 74.5%. Global explanations identified hip and knee weakness, gastrocnemius-soleus contractures, and BMI as the most important predictors across gait patterns. Local explanations illustrated how patient-specific impairments informed individual predictions. The user study demonstrated the clinical utility of the explanations, as they were perceived as interpretable, provided useful insights, and these insights were actionable. The explanations largely aligned with the expectations and increased self-reported trust in the model. Conclusions: Gait patterns in DMD can be predicted from clinically actionable impairments, and explainable artificial intelligence can translate model outputs into meaningful clinical insights. This approach is promising for supporting both general and personalized rehabilitation and orthopedic strategies aimed at prolonging ambulation in DMD. Further validation in larger, multi-center cohorts is needed.

Background and Purpose: Walking after stroke is often characterized by persistent biomechanical impairments and reduced walking capacity. While visual biofeedback can improve gait mechanics and fast walking can enhance capacity, it is unclear whether individuals post-stroke can effectively use biofeedback at higher walking speeds to address both deficits simultaneously. This study examined the effects of walking speed on the ability of participants with chronic stroke to reduce step length (SL) errors using visual biofeedback. Methods: Sixteen individuals with chronic stroke walked on a treadmill at slow, self-selected, and fast speeds with and without visual SL biofeedback. Absolute SL error relative to individualized targets was calculated for paretic and non-paretic limbs. Linear mixed-effects models with piecewise linear splines assessed the effects of speed, limb, and feedback condition. Post hoc comparisons were performed for significant interactions. Results: At lower speeds, increasing speed reduced SL error in both limbs (p < 0.001). At higher speeds, the effects of speed were dependent on limb and condition (p < 0.001). Paretic SL error increased with speed without feedback but remained stable with feedback (p < 0.001). Non-paretic SL error decreased with speed regardless of condition. SL error was greater in the paretic limb overall (p < 0.001). Discussion and Conclusions: Fast walking alone did not reduce paretic SL errors. Participants with chronic stroke can effectively use visual biofeedback to reduce paretic SL errors at higher speeds, supporting its integration into high-intensity gait training to simultaneously treat biomechanical impairments and walking capacity deficits after stroke.

Abstract Background: Stroke is a neurological disorder which is defined as the sudden onset of focused or global disruptions in functions of brain caused due to vascular issue which lasts more than 24 hours or sometimes leading to death. Objective: To determine the effects of multimodal balance training with and without auditory cues on balance, gait mobility, risk of fall and quality of life in patients with chronic stroke. Methodology: This randomized controlled trial, conducted at Islam Teaching Hospital and Idrees Hospital Cant. Sialkot, Pakistan, included 21 stroke survivors per group, 42 in total, (aged 45-70, 1-year post-stroke) using non-probability convenient sampling. Group A received multimodal balance training with auditory cues, while Group B received the same training without cues for 12 weeks. Exclusion criteria included respiratory or orthopedic conditions, cognitive disorders (MMSE < 24), aphasia, non-healing ulcers, or osteoporosis. Outcomes (Berg Balance Scale, Time Up and Go Test, Fall Efficacy Scale-International, Stroke Specific Quality of Life Scale) were assessed at baseline, 6 weeks, and 12 weeks. Results: Group A (with auditory cues) showed statistically significant improvements in balance (Berg Balance Scale: median 21 to 47.5, p < .001), gait mobility (Time Up and Go Test: median 26 to 11 seconds, p < .001), fall risk (Fall Efficacy Scale-International: median 61 to 17, p < .001), and quality of life (Stroke Specific Quality of Life Scale: median 91 to 176.5, p < .001) over 12 weeks, outperforming Group B (without auditory cues) in all measures (p < .001 for balance, gait, and fall risk; p = 0.001 and p < .001 for quality of life at 6 and 12 weeks, respectively). Conclusion: Chronic stroke treatments including multimodal balance training with auditory cues have demonstrated significant advantages over a 12-week therapy session. The results demonstrate significant improvements in balance, gait mobility, risk of fall, and quality of life in chronic stroke survivors. Abbreviations: MMBT (Multimodal Balance Training), MMBTwAC (Multimodal Balance Training with Auditory Cues, referring to Group A), RAS (Rhythmic Auditory Stimulation), RCT (Randomized Controlled Trial), MMSE (Mini-Mental State Examination), BBS (Berg Balance Scale), TUG (Time Up and Go Test), FES-I (Fall Efficacy Scale-International), SSQOL (Stroke-Specific Quality of Life Scale), SPSS (Statistical Package for the Social Sciences), SD (Standard Deviation), and MAS (Modified Ashworth Scale). Key words: Multimodal, Balance, Stroke, Gait, Berg Balance Scale (BBS) and Auditory cues.

Purpose: To explore how 12-weeks of robotic walking impacts physical function and sequelae of inactivity for individuals with pediatric-onset neuromotor impairments. Methods: A single-arm mixed-methods interventional study examined robotic walking for 12-weeks in home and community settings, with 12-week follow-up. Outcomes included family goals (Goal Attainment Scale (GAS)) and perspectives (Interviews), postural control (Early Clinical Assessment of Balance), physical activity (Actigraphy, Habitual Activity Estimation Scale, Patient Reported Outcome Measurement Information System (PROMIS) Physical Activity) and sequelae of inactivity (PROMIS Sleep Disturbances, Bowel Function Diary). GAS was collected pre-training, post-training, and 12-week follow-up. All other quantitative outcomes were collected every 4-weeks. Quantitative data are described with median (25th-75thpercentile) and analyzed using a Skillings-Mack test with post-hoc Wilcoxon Signed-Rank. Qualitative interviews were conducted before and after training and analyzed thematically. Results: 15 participants aged 4-23 completed this study. Participants had cerebral palsy (10/15) or rare genetic conditions (5/15), and most used a wheelchair in community settings. Postural control improved (test-statistic = 23.0, p<0.001) after 8 weeks (change=5.0(0.0-21.4), p=0.016) and was maintained through 12-week follow-up (change=13.7(3.1-23.7), p=0.008). Over half of the participants achieved goals (t-score > 50) after training. Exploratory analyses suggest improvements in sleep disturbance immediately after training (p=0.025) and 4-weeks after (p=0.047). All measures of physical activity did not improve. Parents reported improvements in walking, activities of daily living, and sequelae of inactivity (i.e., bowel function, appetite, and sleep). Conclusions: Improvements were seen across a range of measures and notably postural control improvements were maintained at the follow-up. Parents perceived improvements in physical function and activities of daily living. Future research is warranted to further understand the impacts of robotic walking for children and small adults with mobility impairments.