OBJECTIVE:To estimate the minimal important change (MIC) in the amount of time spent at different physical activity intensities (sedentary behavior [SB], light-intensity physical activity [LPA], and moderate-to-vigorous intensity physical activity [MVPA]) among older patients with subacute stroke undergoing inpatient rehabilitation, in the overall cohort and in subgroups stratified by walking ability. METHODS:This prospective longitudinal observational study enrolled 299 subacute stroke patients from 12 rehabilitation units. SB, LPA, and MVPA were measured using an accelerometer. The average daily time spent in each intensity and Functional Independence Measure (FIM) and FIM-Motor subscale (FIM-M) scores were assessed at admission and 30 days later. Anchor-based improvement was defined as a ≥22-point increase in FIM or ≥17-point increase in FIM-M. Patients were stratified by Functional Ambulation Categories (FAC) as assisted walking (FAC ≤ 2) or unassisted walking (FAC ≥ 3). MICs were estimated using adjusted predictive modeling when the Pearson correlation between physical activity changes and anchor outcomes was ≥0.3. RESULTS:A sufficient correlation was observed only in patients with FAC ≤ 2; thus, MICs were estimated only in this subgroup. MICs based on FIM were -42.1 minutes for SB, 44.4 minutes for LPA, and 2.9 minutes for MVPA. MICs based on FIM-M were -40.7 minutes for SB, 41.5 minutes for LPA, and 2.6 minutes for MVPA. CONCLUSION:MICs for time spent at different physical activity intensities were identified only in older patients with subacute stroke who require walking assistance. These findings provide clinically meaningful reference values for interpreting changes in physical activity during rehabilitation.
BACKGROUND:Fatigue affects 50% to 90% of patients with multiple sclerosis, Parkinson's disease, stroke, ME/CFS, and long COVID and represents a primary barrier to rehabilitation participation yet remains poorly understood despite decades of research. THE PROBLEM:Systematic examination of recent comprehensive reviews reveals a dual diversity failure. Brain diversity is underexamined: fatigue, fundamentally a central nervous system symptom, is assessed predominantly through questionnaires (95%-100% of studies) and peripheral biomarkers, while functional neuroimaging appears in fewer than 15% of studies. Population diversity is neglected: reviews consistently document a predominance of Western European and North American cohorts, with racial and ethnic composition inconsistently reported and demographic stratification virtually absent. THE SOLUTION:Identical fatigue scores reflect heterogeneous brain mechanisms, basal ganglia hypometabolism, frontal dysfunction, inflammatory network disruption, and differentially distributed across populations. Five testable predictions distinguish this framework: (1) neuroimaging reveals distinct subtypes; (2) subtypes show different clinical phenotypes; (3) treatment responses vary by subtype; (4) populations differ in subtype distribution; and (5) stratification resolves apparently inconsistent findings. RECOMMENDATIONS:Fatigue rehabilitation research should (1) incorporate multimodal neuroimaging as standard, with a tiered protocol accommodating participant burden; (2) intentionally recruit demographically diverse populations; (3) employ data-driven clustering to identify brain-based subtypes; and (4) conduct mechanism-stratified treatment trials. An illustrative study design incorporating multimodal neuroimaging, comprehensive clinical and biological assessment, and diverse population sampling can test core predictions within existing research infrastructure. IMPACT:Mechanism-based patient stratification enables precision rehabilitation, reducing required trial sample sizes while identifying effective interventions and preventing harm in vulnerable subgroups.
BACKGROUND:Implanted brain-computer interfaces (iBCIs) can record signals directly from the brain and translate them into computer commands continuously, at high speed and fidelity. Over 150 people worldwide have been implanted with an iBCI, and this number is expected to increase rapidly as iBCIs become commercially available. Despite the progress that is being made in the development of safe, wireless, and highly effective iBCIs, none of these have been implemented in youth or adults with pediatric-onset conditions. OBJECTIVE:Pediatric-onset conditions, such as Cerebral Palsy (CP), represent a large proportion of the global burden of complex and severe disability. Since affected individuals, particularly youth, will likely benefit significantly from iBCIs, they should not be left behind in technological progress that would be life-changing. We outlined the evidence gaps, steps required, and arguments for greater focus on this population in iBCI research and development. METHODS:Here, we present the result of two years of cumulative effort, combining expert opinions and findings from multiple transdisciplinary engagement sessions, including the first International Virtual Summit on Implanted BCIs for Children with Complex Needs, follow-up themed workgroup sessions, and a final in-person workshop held at the 11th International BCI Society Meeting. RESULTS:We established a world-first visionary, community-and-partner-engaged roadmap for the design, development, and implementation of iBCIs for youth with CP to meaningfully interact with the world. CONCLUSIONS:Developing iBCI systems for youth with CP requires a fundamental shift toward child‑centric neuroscience, engineering, and user‑driven design rather than adapting adult‑oriented technologies.
INTRODUCTION:Millions of stroke survivors in the US have sensory-motor impairments that significantly impact quality of life and place a long-term burden on families, communities, and the healthcare system. Neurorehabilitation aims to improve function, typically through repetitive practice of movements and task-related activities where doses are regularly titrated by skilled clinicians. Unfortunately, these highly intensive, skilled interventions are challenging to implement at the scale needed to serve the needs of stroke survivors. Rehabilitation technologies have long promised to be the workforce multiplier to normalize this large supply-demand mismatch in the U.S. healthcare system. Extensive investigations into rehabilitation devices have revealed myriad benefits. While rehab technologies have the potential to improve function, these inferences are largely derived from academic clinical studies which, while useful for exploring efficacy, do not represent marketplace (ie, commercial) conditions where interventions must operate to serve the larger population. METHODS:Here, we present data from the first nationwide direct-to-consumer deployment of 2 home-based rehabilitation robotic systems. RESULTS:Analysis of 3182 device deployments from August 2019 to June 2024 reveal surprising patterns in usage and compliance. We investigate the effects of socio-economic status, sex, rural-urban classification, and engagement on long-term utilization. Finally, we provide preliminary dose-response insights. DISCUSSION AND CONCLUSIONS:We discuss the influence of market forces on commercial delivery of care to inform stakeholders of the challenges faced translating interventions to the consumer. Overall, we aim to derive lessons that can guide future implementations and improve the inclusivity and effectiveness of rehabilitation technologies deployed at scale.
Implantable brain-computer interfaces (iBCIs) are at a pivotal inflection point. Multiple commercial ventures are advancing toward regulatory approval, and the challenge facing the field is transitioning from demonstrating safety and feasibility to achieving regulatory approval, reimbursement by payors, and sustainable clinical integration. Central to this challenge is the urgent need for robust, valid, and reliable clinical outcome assessments (COAs) that satisfy both regulatory and payor requirements and meaningfully reflect the lived experiences of people with severe motor impairment. Without such measures, iBCIs risk stalling in the transition from early feasibility to reimbursable therapy.
BACKGROUND:Implementing intensive motor skill learning interventions like Hand-Arm Bimanual Intensive Therapy Including Lower Extremities (HABIT-ILE) in clinical practice faces accessibility challenges. Integrating the interactive virtual device (REAtouch®) into HABIT-ILE may help overcome these barriers, with potential for remote use. OBJECTIVE:This study aimed to investigate whether HABIT-ILE with REAtouch® has non-inferior results compared to usual HABIT-ILE in children with bilateral cerebral palsy (BCP). METHODS:Thirty children with BCP were randomized into the REAtouch® group (using the device for half of the one-to-one intervention time) or the HABIT-ILE group. Both groups completed a 65-hour intervention over 2 weeks. Assessments were conducted at baseline, post-intervention, and follow-up using primary (Gross Motor Function Measure [GMFM-66] and ABILHAND-Kids) and secondary measures. Analyses included one-way RM ANOVA, Friedman Test, and non-inferiority statistics. RESULTS:Non-inferiority analysis indicated that the REAtouch® group did not achieve non-inferior changes compared with usual HABIT-ILE for most primary and secondary outcomes at post-intervention and follow-up (p > 0.025). Although both groups demonstrated statistically significant improvements in primary and most secondary outcomes, non-inferiority was confirmed only for ABILHAND-Kids (P = .022) and JTTHF-MA (P = 0.021) at post-intervention. CONCLUSION:While both groups improved in motor functions and daily life abilities, integrating REAtouch® into HABIT-ILE may not allow achieving non-inferior changes compared to usual HABIT-ILE in children with BCP. This highlights the role of virtual devices like REAtouch® as complementary tools rather than replacements for evidence-based therapy, with potential to enhance accessibility through carefully implemented remote use. CLINICAL TRIAL REGISTRATION NUMBER:NCT04403464.
BACKGROUND:Concussions in adolescents, especially in sports, represent a major public health issue due to prolonged recovery and diagnostic challenges compared to adults. Current clinical assessments often underestimate the true burden and recovery course, highlighting the need for objective physiological biomarkers. OBJECTIVE:To investigate heart rate variability (HRV) as a potential biomarker for monitoring concussion recovery in adolescents through both traditional statistics and machine learning approaches. METHODS:Thirty-seven concussed adolescents (23 females, 14 males; mean age 15 ± 2 years) and 37 age-matched healthy controls (14 females, 23 males; mean age 16 ± 2 years) were enrolled. Concussed participants were evaluated within 1 month post-injury and at clinical discharge (mean interval = 9 ± 4 days). Each session included a 5-minute electrocardiogram and Post-Concussion Symptom Scale (PCSS). Time-domain HRV metrics-standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive differences (RMSSD), were severity-adjusted to PCSS severity (SDNNidx, RMSSDidx). A Boosted Tree algorithm predicted clinical outcomes (Good/Bad) based on raw and severity-adjusted HRV features. RESULTS:Conventional statistics revealed no significant group differences in raw HRV metrics. However, severity-adjusted indices increased with lower symptom severity. The optimized Boosted Tree model achieved promising discriminative performance (AUC = .88), with 82% to 83% sensitivity, 75% to 79% specificity, and 82% to 84% F1 scores, accurately classifying all controls. CONCLUSIONS:Machine learning uncovered nonlinear HRV patterns predictive of clinical recovery where standard analyses failed. HRV-based predictive modeling may provide a noninvasive approach for individualized autonomic monitoring and evidence-based concussion management in adolescents.
Introduction: Accurate evaluation of upper limb recovery after stroke is essential for guiding rehabilitation targeting specific impairments and activity limitations. To achieve this, outcome measures must clearly reflect what they assess, whether neuromuscular impairments or activity limitations. However, classification of measures is not always clear-cut, which can lead to misinterpretation of recovery progress and reduce rehabilitation planning effectiveness. Problem: Current classification practices often prioritize item content over the scoring criteria that define what is being quantified. This becomes particularly problematic when task-based items are scored using impairment-oriented criteria (e.g., range of motion), blurring whether change reflects impairment recovery or activity-level improvement. This ambiguity can mislead clinical decision-making and the interpretation of research findings. Solution: We propose a construct-driven application of the International Classification of Functioning, Disability and Health (ICF) in which component-level attribution is determined by the construct operationalized through scoring rather than inferred from item content. As scoring structures differ, three strategies are suggested based on item-level scoring attribution where feasible: (1) proportional classification for measures in which one ICF component predominates (with a pragmatic, provisional ≥60% dominance guideline for near-boundary cases), otherwise (2) dual-component reporting for mixed measures; and (3) non-proportional interpretation for measures exhibiting construct shifting across score levels or using dominant-construct scoring with embedded grading criteria. Conclusion: Grounding classification in the construct operationalized by scoring criteria provides a more defensible basis for outcome selection and interpretation. This supports clearer interpretation of intervention effects, more targeted rehabilitation, and stronger comparability across trials and evidence synthesis.
Abnormal synergies coexist with primary motor impairments (weakness and spasticity) after stroke. They are observed during voluntary movements and are characterized by stereotyped movement patterns, a loss of independent joint control, and abnormal muscle coordination (eg, involuntary activation of distal muscles led by proximal joint movement). The structure and expression of abnormal synergies, however, are highly context-dependent (eg, influenced by gravity, body posture, and task constraints) and are not homogeneous across patients. Current evidence suggests that abnormal synergies are pathophysiologically related to damage to corticospinal tracts, upregulation of brainstem pathways (particularly the medial reticulospinal tract, but also involves the vestibulospinal tract), and maladaptive changes in spinal circuitry. These same mechanisms may overlap with those underlying spasticity and weakness. Spasticity is believed to result from overexcitability of descending excitatory brainstem pathways, the reticulospinal tract in particular, and the consequent exaggerated stretch reflexes, while muscle weakness is attributed to the reduction in corticospinal output. Recent research and clinical observations have advanced our understanding of abnormal synergies. Post-stroke abnormal synergies are not fixed motor impairments. A new framework is proposed that suggests post-stroke abnormal synergies could constitute the behavioral expression of primary impairments, including weakness and spasticity, arising from their interactions with environmental constraints, particularly antigravity control mechanisms. The term "synergy" has been used across various frameworks, with different definitions and quantification approaches. Identifying appropriate methods to quantify abnormal synergies is therefore essential to investigate their relationship with spasticity and muscle weakness, and evaluate potential abnormal synergy improvements following interventions, even if they primarily target other motor impairments.
INTRODUCTION:Postural balance dysfunction in Parkinson's disease (PD) is associated with sensory integration deficits, yet stage-related changes and their relationship with falls remain incompletely understood. This study evaluated sensory integration across Hoehn-Yahr stages and prospectively monitored falls over 6 months. METHODS:Seventy-five PD patients (26 early-stage and 49 advanced-stage) and 26 healthy controls (HCs) were assessed using the Sensory Organization Test. Demographic and motor assessments were performed, and falls were tracked for 6 months. Group comparisons used 1-way analysis of variance or Kruskal-Wallis tests, as appropriate. Associations with fall status were analyzed using χ² tests. RESULTS:Advanced-stage PD patients were older and exhibited more severe motor symptoms than early-stage patients. Sensory integration deteriorated with disease progression. Compared with HCs and early-stage PD patients, advanced-stage PD patients demonstrated significantly reduced composite balance scores (P < .001). Significant overall group differences were observed for visual (P = .029), vestibular (P < .001), and preference ratios (P < .001), whereas somatosensory ratios remained preserved. Falls occurred in 33.3% of PD patients and were more frequent in advanced stages (44.9% vs 11.5%; P < .001). Vestibular dysfunction was significantly associated with fall occurrence (76.0% vs 38.0%; P = .002). CONCLUSION:Sensory integration deficits in PD progress with disease advancement and are primarily characterized by impairments in visual and vestibular domains. Vestibular dysfunction was significantly associated with fall risk. These findings suggest that vestibular assessment and targeted interventions may be beneficial for fall-risk management in PD.
BACKGROUND:Reliable prediction of upper-limb recovery after stroke can support rehabilitation planning, yet few prognostic models have been tested beyond their development cohorts. External validation is essential to establish the clinical reliability of these methods. OBJECTIVE:To externally validate a previously developed machine learning model for predicting 6-month upper-limb capacity after stroke, measured by the Action Research Arm Test (ARAT). METHODS:The model was developed on a multicentre Dutch cohort of first-ever ischaemic stroke patients and validated in an independent Danish prospective cohort, including both ischaemic and haemorrhagic strokes. Predictions were generated from baseline assessments at 2 weeks post-stroke. Model performance was evaluated using the median absolute error (MedAE) and calibration analysis. RESULTS:The validation cohort comprised 80 patients assessed at 14 ± 4 days post-stroke. Overall prediction error was comparable between the validation and development cohorts (MedAE = 5.7 [IQR 1.9-15.1] vs 3.9 [IQR 1.1-13.0]; P = 0.12). Calibration was close to ideal for predicted ARAT scores above 40. In contrast, lower predicted ranges showed systematic underprediction, reflecting variable outcomes in severely impaired patients, a pattern similar to that observed in the development cohort. CONCLUSIONS:In an independent validation cohort, the machine learning model performed similarly to its development cohort but showed clinically relevant miscalibration in patients with low predicted ARAT scores. Inclusion of additional predictors is required to improve reliability in severely impaired patients before subsequent steps toward clinical implementation can be considered.
BACKGROUND:Compensatory movement strategies are common after stroke and vary across individuals and tasks. However, the lack of a structured framework to guide movement analysis during mobility and postural control tasks may limit consistent identification of these strategies across clinicians in clinical practice. OBJECTIVE:To develop and examine the content validity of the Movement Compensatory Screening (MoCS) to identify compensatory movement strategies during mobility and postural control tasks after stroke. METHODS:Following the Delphi method and COSMIN guidelines, the MoCS was developed through a multi-phase process. Item generation was based on a literature review, exploratory video analysis of individuals after stroke, and expert input. Item-level content validity was evaluated in 2 Delphi rounds using relevance and clarity ratings (Content Validity Coefficient ≥ 0.80). Instrument-level content comprehensiveness was subsequently assessed through a Delphi-based global evaluation by physiotherapists. RESULTS:The final MoCS comprised 65 items across 7 domains: sit-to-stand and stand-to-sit transfer, gait, turn, climb up/down stairs, and dynamic standing balance. Initial mean CVC values were 0.89 for relevance and 0.86 for clarity, leading to item exclusion or refinement. Revised items achieved mean CVC values of 0.93 and 0.88 and were retained. An instrument-level evaluation indicated adequate content comprehensiveness, with expert agreement that the final item set sufficiently covered compensatory movement domains. A compensatory index (CI) was used to describe compensatory strategies by domain and anatomical plane. CONCLUSION:The MoCS demonstrated content validity as an observational framework for identifying compensatory movement strategies during mobility and postural control tasks after stroke.
BACKGROUND:Children with unilateral spastic cerebral palsy (USCP) exhibit altered corticospinal organization that may influence responsiveness to treatment. Transcranial direct current stimulation (tDCS) may modulate corticospinal excitability, though responses vary widely. Recruitment curves derived from transcranial magnetic stimulation (TMS) can quantify excitability changes. OBJECTIVE:To evaluate the feasibility, safety, and preliminary effects of combined TMS and anodal tDCS on recruitment curve-derived corticospinal excitability in children with USCP and explore predictors of responsiveness. METHODS:In a single-group pre/post study, 20 children with USCP completed TMS-evoked recruitment curve testing before and after 20 minutes of 2mA anodal tDCS. Primary outcomes included changes in S50 (half-maximal motor-evoked potential [MEP] intensity) and slope at the curve inflection point. Secondary outcomes included MEP amplitude-based and model-derived recruitment curve metrics. Safety and tolerability were assessed using a standardized symptom screen. RESULTS:The protocol was well-tolerated: no serious adverse events occurred, 80% reported no symptoms, and the most common symptom was mild scalp itching. No significant group-level pre/post differences were observed in this preliminary study. Responses were heterogeneous: 11/20 children met the responder definition (ΔS50 < 0). Exploratory analyses identified no consistent clinical or neurophysiologic predictors, although a potential responder pattern was observed in participants with bilateral corticospinal tract patterns. CONCLUSIONS:Although uniform group-level excitability changes were not observed following a single session of 2mA anodal tDCS, recruitment curve metrics were feasible, well-tolerated, and sensitive to interindividual differences. These findings support the use of recruitment curves as feasible tools to characterize variability and inform individualized neuromodulation strategies.Trial registration number: NCT03402854.
BACKGROUND:Spinal cord injury (SCI) leads to lifelong disability with highly variable neurological recovery, complicating prognostication and conceptualization of clinical trials. The American Spinal Injury Association Impairment Scale (AIS) is widely used to classify injury severity. Although AIS A injuries are considered sensorimotor complete, they show substantial heterogeneity in residual function and recovery. Data-driven approaches offer an opportunity to uncover latent subgroups beyond conventional classifications. We evaluate whether unsupervised, data-driven clustering can identify distinct subgroups within patients with traumatic SCI and characterize neurological patterns in sensorimotor complete SCI. METHODS:We applied an unsupervised clustering model to International Standards of Neurological Classification of Spinal Cord Injury (ISNCSCI) examination scores from the European Multicenter Study about Spinal Cord Injury dataset (3165 patients), to derive neurological groupings independent of predefined ISNCSCI classifications. Clusters were derived from the full cohort, followed by focused analyses of individuals classified as AIS A at their first documented assessment. External reproducibility was evaluated using data from the Sygen clinical trial. RESULTS:Six distinct clusters were identified. Patients graded as AIS A were represented in 5 clusters, which differed markedly in injury level (paraplegic vs tetraplegic) and indicators of recovery potential, including neurological sparing, upper and lower extremity motor scores, and AIS conversion rates. These patterns were consistently reproduced in the Sygen cohort. CONCLUSIONS:Proposed framework complements conventional AIS grading by revealing distinct neurological conditions related to the variability among patients with baseline sensorimotor complete injuries. Proposed data-driven framework enables more comprehensive prognostic assessments and improves patient stratification in clinical trials.
BACKGROUND:Children with cerebral palsy (CP) have impaired motor and simplified neuromuscular control during walking. Surgical interventions, conventional therapies, and real-time biofeedback result in minimal improvements in muscle synergies, highlighting the need for new strategies to enhance motor control. OBJECTIVE:To assess how neuromuscular control of the more-affected limb is acutely affected across walking environments and speeds for children with CP. METHOD:Eight children with CP (5 males and 3 females; age: 12.58 ± 3.91 years; height: 1.52 ± 0.20 m; and weight: 54.55 ± 30.83 kg) and 15 typically developing children had 8 surface EMG sensors on the lower limbs. Muscle synergies were calculated with non-negative matrix factorization to define dynamic motor control during walking (walk-DMC) for overground, conventional treadmill, and aquatic treadmill walking. We compared walk-DMC across environment and speed conditions (slow, normal, and fast) for the more-affected limb. RESULTS:Main effects of the aquatic environment and the slow walking speed acutely increased walk-DMC in children with CP, indicating increased neuromuscular complexity. Neither conventional treadmill nor overground environments significantly impacted walk-DMC scores. CONCLUSIONS:Walk-DMC was sensitive to acute changes in the walking environment and speed in children with CP. These findings offer new perspectives on walking rehabilitation by accounting for the interplay between task demands and motor function. However, future studies should investigate repeated exposures to aquatic gait rehabilitation environments, particularly aquatic treadmill training and slow walking speeds.
High-intensity training (HIT) focused on stepping practice consistently improves clinical locomotor outcomes in individuals with neurologic injury. However, traditional HIT approaches typically do not target underlying impairments, and gains in non-locomotor tasks (ie, balance and transfers) or daily stepping are limited. One strategy to address these limitations involves providing HIT in variable contexts by progressively increasing locomotor demands across diverse environments while targeting specific biomechanical deficits (ie, limb-swing, propulsion, stance, and postural stability). This approach parallels the concept of "shaping" used successfully in constraint-induced movement therapy trials pioneered by Dr. Steven Wolf. The rapid progression of variable, difficult stepping tasks during HIT produces gains in multiple locomotor and non-locomotor outcomes, although, importantly, the accelerated progression of task demands and acceptance of movement variability represent key departures from conventional rehabilitation frameworks emphasizing gait quality. Together, this focus on progression and variability is likely responsible for the observed gains. In this issue honoring Dr. Steven Wolf, we delineate the shaping principles applied to locomotor rehabilitation following neurologic injury. We outline the rationale for HIT in variable contexts, explain how biomechanical targeting guides intervention progression, and present evidence detailing its observed efficacy in improving clinical and community mobility outcomes. We also describe how advanced robotic technology can further enhance locomotor outcomes by applying progressive resistance to target specific locomotor deficits. By integrating principles of biomechanics with long-standing theories in motor learning, we believe HIT in variable contexts can further harness the neural plasticity of the nervous system to maximize locomotor function following neurologic injury.
BACKGROUND:While non-invasive electrical stimulation is used clinically to enhance motor performance, its efficacy and mechanisms remain unclear. Studies show that personal factors, such as beliefs and expectations of stimulation, can impact how much a person benefits from the stimulation itself. Furthermore, beliefs related to the "closeness is strength of effect" have been observed outside of electrical stimulation contexts, suggesting that the location of stimulation (eg, head and neck) for improving motor performance may impact how much they believe the stimulation will work. This exploratory study investigated beliefs about the optimal target region of stimulation for maximizing the effect of stimulation itself. METHODS:Eighty participants (39 females; 46.9 ± 12.6 years) completed an online spatial mapping task in which they were asked to indicate where they would place the electrodes for electrical stimulation to hypothetically enhance specific functions: "hand movement," "arm movement," "leg movement," and "attention/concentration." Participants selected their placement by clicking a blank human figure in anatomical position. Information about prior use/knowledge of non-invasive stimulation was also collected. RESULTS:Optimal target region of stimulation was significantly associated with the body movement/function to be enhanced (P < .001). This association was independent of prior non-invasive stimulation knowledge (P = .242) and sex (P = .923). CONCLUSIONS:These findings suggest a pre-existing belief of spatial proximity for electrical stimulation in which placing electrodes closer to the body region of interest would maximize improvement hypothetically.
INTRODUCTION:Individuals with motor incomplete spinal cord injury (iSCI) have difficulty eliciting reactive steps when balance is lost, increasing fall risk. Functional electrical stimulation (FES) applied to the common fibular nerve elicits a flexor withdrawal response, potentially assisting reactive stepping. Combining reactive balance training with FES (Reactive Balance Training [RBT] + FES) may enhance reactive balance control. This study compared the efficacy of RBT + FES to RBT alone in individuals with chronic, motor iSCI. METHODS:Twenty-two individuals (63.9 ± 14.8 years; 3.8 ± 2.8 years post-injury) were randomly assigned to RBT + FES or RBT alone. They completed 18 1-hour training sessions over 6 weeks. Outcome measures were assessed pre-, immediately post- and 6 months post-intervention, and included the behavioural response of the Lean-and-Release test (single-step, 2-step, ≥3-step, or fall) and clinical measures of balance, balance confidence, fall concern, lower limb strength, and proprioception of the ankle. A 2-way mixed analysis of variance assessed group differences over time. Fall incidence was monitored via an online survey for 6 months following training. RESULTS:Significant improvements over time were observed for single-step and fall responses during the Lean-and-Release test, and on all clinical outcomes (P ≤ .01) with the exception of ankle proprioception. No significant group or group × time interactions were found, suggesting similar improvements between groups. There were no significant between-group differences in fall tracking data. DISCUSSION:Both RBT + FES and RBT alone led to significant improvements in reactive stepping ability, balance control, balance confidence, fall concern, and lower limb strength. However, the FES protocol applied in this study did not provide additional benefit.
Purpose: Progressive disability occurs in persons with amyotrophic lateral sclerosis (pALS), but change over time across phenotypes remains understudied, limiting clinical decision-making. This descriptive study describes functional motor change with detailed measures across ALS phenotypes to enhance clinical decision making. Materials and Methods: Electronic health record data from an interdisciplinary ALS clinic (n = 109 pALS, 2018-2022) including demographics, disability (ALS Functional Rating Scale-[ALSFRS-R]), and functional motor scores (10 m Walk, Handheld dynamometry [grip and ankle]) was utilized. Phenotype groups were defined by site of onset (bulbar, limb onset; upper limb or lower limb). Analysis was conducted using R and included changes scores and measures of central tendency in 3-month intervals. Results: PALS included n = 43 bulbar, n = 32 upper limb, n = 34 lower limb onset, age 65, 60 to 71 (median, interquartile range). ALFSRS-R decline was greatest in bulbar, and similar in upper and lower limb. Patterns of change within motor scores suggest greatest loss of grip strength in bulbar and upper limb, ankle strength in upper limb, walking speed in lower limb, and preservation of community ambulation in upper limb. Conclusion: While ALSFRS-R scores were similar in upper and lower limb, detailed functional motor measures indicated differences in groups. These patterns provide insight to guide clinical decision making and future research to enhance care in pALS.
