Single-belt vs. split-belt treadmill symmetry training: is there a perfect choice for gait rehabilitation post-stroke?

Post-stroke gait asymmetry leads to inefficient gait and a higher fall risk, often causing limited home and community ambulation. Two types of treadmills are typically used for training focused on symmetry: split-belt and single belt treadmills, but there is no consensus on which treadmill is superior to improve gait symmetry in individuals with stroke. To comprehensively determine which intervention is superior, we considered multiple spatial and temporal gait parameters (step length, stride time, swing time, and stance time) and their symmetries. Ten individuals with stroke underwent a single session of split-belt treadmill training and single belt treadmill training on separate days. The changes in step length, stride time, swing time, stance time and their respective symmetries were compared to investigate which training improves both spatiotemporal gait parameters and symmetries immediately after the intervention and after 5 min of rest. Both types of treadmill training immediately increased gait velocity (0.08 m/s faster) and shorter step length (4.15 cm longer). However, split-belt treadmill training was more effective at improving step length symmetry (improved by 27.3%) without sacrificing gait velocity or step length. However, this step length symmetry effect diminished after a 5-min rest period. Split-belt treadmill training may have some advantages over single belt treadmill training, when targeting step length symmetry. Future research should focus on comparing the long-term effects of these two types of training and examining the duration of the observed effects to provide clinically applicable information.

Assessing actigraphy performance for daytime sleep detection following stroke: insights from inpatient monitoring in a rehabilitation hospital.

Study Objectives: Stroke can result in or exacerbate various sleep disorders. The presence of behaviors such as daytime sleepiness poststroke can indicate underlying sleep disorders which can significantly impact functional recovery and thus require prompt detection and monitoring for improved care. Actigraphy, a quantitative measurement technology, has been primarily validated for nighttime sleep in healthy adults; however, its validity for daytime sleep monitoring is currently unknown. Therefore this study aims to identify the best-performing actigraphy sensor and algorithm for detecting daytime sleep in poststroke individuals. Methods: Participants wore Actiwatch Spectrum and ActiGraph wGT3X-BT on their less-affected wrist, while trained observers recorded daytime sleep occurrences and activity levels (active, sedentary, and asleep) during non-therapy times. Algorithms, Actiwatch (Autoscore AMRI) and ActiGraph (Cole-Kripke, Sadeh), were compared with on-site observations and assessed using F2 scores, emphasizing sensitivity to detect daytime sleep. Results: Twenty-seven participants from an inpatient stroke rehabilitation unit contributed 173.5 hours of data. The ActiGraph Cole-Kripke algorithm (minute sleep time = 15 minutes, bedtime = 10 minutes, and wake time = 10 minutes) achieved the highest F2 score (0.59). Notably, when participants were in bed, the ActiGraph Cole-Kripke algorithm continued to outperform Sadeh and Actiwatch AMRI, with an F2 score of 0.69. Conclusions: The study demonstrates both Actiwatch and ActiGraph's ability to detect daytime sleep, particularly during bed rest. ActiGraph (Cole-Kripke) algorithm exhibited a more balanced sleep detection profile and higher F2 scores compared to Actiwatch, offering valuable insights for optimizing daytime sleep monitoring with actigraphy in stroke patients.

Developing a mobile exercise program for individuals with Spinal Cord Injury: Stakeholder perceptions of app features and implementation determinants.

BACKGROUND: Individuals with Spinal Cord Injury (SCI) often experience physical deconditioning, leading to long-term health challenges. While regular exercise can offer substantial health benefits, adherence to exercise guidelines among individuals with SCI is hindered by barriers such as inaccessibility. Exercise programs using the mobile application (App) tailored to individual needs present a promising solution for promoting exercise adherence among individuals with SCI. OBJECTIVE: This study aimed to identify factors contributing to the successful implementation of an app-based home exercise program for individuals with SCI and gather user feedback on app preferences, functionality, and features. METHODS: Guided by the Consolidated Framework for Implementation Research (CFIR), twenty-six clinicians completed an expert panel survey to rank factors influencing the implementation of an app-based intervention for increasing exercise adherence for individuals with SCI. CFIR-selected factors and app quality features obtained from the Mobile Application Rating Scale (MARS) framework were discussed in seven focus groups with 23 individuals with SCI, 6 caregivers, and 6 clinicians. RESULTS: The expert survey identified adaptability, complexity, evidence strength/quality, relative advantage, knowledge/beliefs about the initiative, and execution as the key CFIR factors that affected the intervention's success. Major themes emerging from focus groups with individuals with SCI and caregivers included usability, instruction and guidelines, user-friendly interface, and clinician interaction. In contrast, clinicians mentioned themes such as the representation of the SCI population, time commitment, accessibility, and equipment. CONCLUSIONS: The study highlights the significance of incorporating these determinants into future designs to develop app-based home exercise interventions for individuals with SCI.

Combining Neuromodulation Strategies in Spinal Cord Injury Gait Rehabilitation: A Proof Of Concept, Randomized, Crossover Trial.

OBJECTIVES: To evaluate if acute intermittent hypoxia (AIH) coupled with transcutaneous spinal cord stimulation (tSCS) enhances task-specific training and leads to superior and more sustained gait improvements as compared with each of these strategies used in isolation in persons with chronic, incomplete spinal cord injury. DESIGN: Proof of concept, randomized crossover trial. SETTING: Outpatient, rehabilitation hospital. INTERVENTIONS: Ten participants completed 3 intervention arms: (1) AIH, tSCS, and gait training (AIH + tSCS); (2) tSCS plus gait training (SHAM AIH + tSCS); and (3) gait training alone (SHAM + SHAM). Each arm consisted of 5 consecutive days of intervention with a minimum of a 4-week washout between arms. The order of arms was randomized. The study took place from December 3, 2020, to January 4, 2023. MAIN OUTCOME MEASURES: 10-meter walk test at self-selected velocity (SSV) and fast velocity, 6-minute walk test, timed Up and Go (TUG) and secondary outcome measures included isometric ankle plantarflexion and dorsiflexion torque RESULTS: TUG improvements were 3.44 seconds (95% CI: 1.24-5.65) significantly greater in the AIH + tSCS arm than the SHAM AIH + tSCS arm at post-intervention (POST), and 3.31 seconds (95% CI: 1.03-5.58) greater than the SHAM + SHAM arm at 1-week follow up (1WK). SSV was 0.08 m/s (95% CI: 0.02-0.14) significantly greater following the AIH + tSCS arm than the SHAM AIH + tSCS at POST. Although not significant, the AIH + tSCS arm also demonstrated the greatest average improvements compared with the other 2 arms at POST and 1WK for the 6-minute walk test, fast velocity, and ankle plantarflexion torque. CONCLUSIONS: This pilot study is the first to demonstrate that combining these 3 neuromodulation strategies leads to superior improvements in the TUG and SSV for individuals with chronic incomplete spinal cord injury and warrants further investigation.

Safety & efficacy of a robotic hip exoskeleton on outpatient stroke rehabilitation.

OBJECTIVE: The objective of this study was to analyze the safety and efficacy of using a robotic hip exoskeleton designed by Samsung Electronics Co., Ltd., Korea, called the Gait Enhancing and Motivating System-Hip (GEMS-H), in assistance mode only with the poststroke population in an outpatient-rehabilitation setting. METHODS: Forty-one participants with an average age of 60 and average stroke latency of 6.5 years completed this prospective, single arm, interventional, longitudinal study during the COVID-19 pandemic. Significant modifications to the traditional outpatient clinical environment were made to adhere to organizational physical distancing policies as well as guidelines from the Centers for Disease Control. All participants received gait training with the GEMS-H in assistance mode for 18 training sessions over the course of 6-8 weeks. Performance-based and self-reported clinical outcomes were assessed at four time points: baseline, midpoint (after 9 training sessions), post (after 18 training sessions), and 1-month follow up. Daily step count was also collected throughout the duration of the study using an ankle-worn actigraphy device. Additionally, corticomotor excitability was measured at baseline and post for 4 bilateral lower limb muscles using transcranial magnetic stimulation. RESULTS: By the end of the training program, the primary outcome, walking speed, improved by 0.13 m/s (p < 0.001). Secondary outcomes of walking endurance, balance, and functional gait also improved as measured by the 6-Minute Walk Test (47 m, p < 0.001), Berg Balance Scale (2.93 points, p < 0.001), and Functional Gait Assessment (1.80 points, p < 0.001). Daily step count significantly improved with and average increase of 1,750 steps per day (p < 0.001). There was a 35% increase in detectable lower limb motor evoked potentials and a significant decrease in the active motor threshold in the medial gastrocnemius (-5.7, p < 0.05) after training with the device. CONCLUSIONS: Gait training with the GEMS-H exoskeleton showed significant improvements in walking speed, walking endurance, and balance in persons with chronic stroke. Day-to-day activity also improved as evidenced by increased daily step count. Additionally, corticomotor excitability changes suggest that training with this device may help correct interhemispheric imbalance typically seen after stroke. TRIAL REGISTRATION: This study is registered with ClinicalTrials.gov (NCT04285060).

Implementation of a unilateral hip flexion exosuit to aid paretic limb advancement during inpatient gait retraining for individuals post-stroke: a feasibility study.

BACKGROUND: During inpatient rehabilitation, physical therapists (PTs) often need to manually advance patients' limbs, adding physical burden to PTs and impacting gait retraining quality. Different electromechanical devices alleviate this burden by assisting a patient's limb advancement and supporting their body weight. However, they are less ideal for neuromuscular engagement when patients no longer need body weight support but continue to require assistance with limb advancement as they recover. The objective of this study was to determine the feasibility of using a hip flexion exosuit to aid paretic limb advancement during inpatient rehabilitation post-stroke. METHODS: Fourteen individuals post-stroke received three to seven 1-hour walking sessions with the exosuit over one to two weeks in addition to standard care of inpatient rehabilitation. The exosuit assistance was either triggered by PTs or based on gait events detected by body-worn sensors. We evaluated clinical (distance, speed) and spatiotemporal (cadence, stride length, swing time symmetry) gait measures with and without exosuit assistance during 2-minute and 10-meter walk tests. Sessions were grouped by the assistance required from the PTs (limb advancement and balance support, balance support only, or none) without exosuit assistance. RESULTS: PTs successfully operated the exosuit in 97% of sessions, of which 70% assistance timing was PT-triggered to accommodate atypical gait. Exosuit assistance eliminated the need for manual limb advancement from PTs. In sessions with participants requiring limb advancement and balance support, the average distance and cadence during 2-minute walk test increased with exosuit assistance by 2.2 ± 3.1 m and 3.4 ± 1.9 steps/min, respectively (p < 0.017). In sessions with participants requiring balance support only, the average speed during 10-meter walk test increased with exosuit by 0.07 ± 0.12 m/s (p = 0.042). Clinical and spatiotemporal measures of independent ambulators were similar with and without exosuit (p > 0.339). CONCLUSIONS: We incorporated a unilateral hip flexion exosuit into inpatient stroke rehabilitation in individuals with varying levels of impairments. The exosuit assistance removed the burden of manual limb advancement from the PTs and resulted in improved gait measures in some conditions. Future work will understand how to optimize controller and assistance profiles for this population.

Detecting the symptoms of Parkinson's disease with non-standard video.

BACKGROUND: Neurodegenerative diseases, such as Parkinson's disease (PD), necessitate frequent clinical visits and monitoring to identify changes in motor symptoms and provide appropriate care. By applying machine learning techniques to video data, automated video analysis has emerged as a promising approach to track and analyze motor symptoms, which could facilitate more timely intervention. However, existing solutions often rely on specialized equipment and recording procedures, which limits their usability in unstructured settings like the home. In this study, we developed a method to detect PD symptoms from unstructured videos of clinical assessments, without the need for specialized equipment or recording procedures. METHODS: Twenty-eight individuals with Parkinson's disease completed a video-recorded motor examination that included the finger-to-nose and hand pronation-supination tasks. Clinical staff provided ground truth scores for the level of Parkinsonian symptoms present. For each video, we used a pre-existing model called PIXIE to measure the location of several joints on the person's body and quantify how they were moving. Features derived from the joint angles and trajectories, designed to be robust to recording angle, were then used to train two types of machine-learning classifiers (random forests and support vector machines) to detect the presence of PD symptoms. RESULTS: The support vector machine trained on the finger-to-nose task had an F1 score of 0.93 while the random forest trained on the same task yielded an F1 score of 0.85. The support vector machine and random forest trained on the hand pronation-supination task had F1 scores of 0.20 and 0.33, respectively. CONCLUSION: These results demonstrate the feasibility of developing video analysis tools to track motor symptoms across variable perspectives. These tools do not work equally well for all tasks, however. This technology has the potential to overcome barriers to access for many individuals with degenerative neurological diseases like PD, providing them with a more convenient and timely method to monitor symptom progression, without requiring a structured video recording procedure. Ultimately, more frequent and objective home assessments of motor function could enable more precise telehealth optimization of interventions to improve clinical outcomes inside and outside of the clinic.

Wireless wearable sensors can facilitate rapid detection of sleep apnea in hospitalized stroke patients.

STUDY OBJECTIVES: To evaluate wearable devices and machine learning for detecting sleep apnea in patients with stroke at an acute inpatient rehabilitation facility (IRF). METHODS: A total of 76 individuals with stroke wore a standard home sleep apnea test (ApneaLink Air), a multimodal, wireless wearable sensor system (ANNE), and a research-grade actigraphy device (ActiWatch) for at least one night during their first week after IRF admission as part of a larger clinical trial. Logistic regression algorithms were trained to detect sleep apnea using biometric features obtained from the ANNE sensors and ground truth apnea rating from the ApneaLink Air. Multiple algorithms were evaluated using different sensor combinations and different apnea detection criteria based on the Apnea-Hypopnea Index (AHI≥5, AHI≥15). RESULTS: Seventy-one (96%) participants wore the ANNE sensors for multiple nights. In contrast, only forty-eight participants (63%) could be successfully assessed for OSA by ApneaLink; 28 (37%) refused testing. The best-performing model utilized photoplethysmography (PPG) and finger temperature features to detect moderate-severe sleep apnea (AHI≥15), with 88% sensitivity and a positive likelihood ratio (LR+) of 44.00. This model was tested on additional nights of ANNE data achieving 71% sensitivity (10.14 LR+) when considering each night independently and 86% accuracy when averaging multi-night predictions. CONCLUSIONS: This research demonstrates the feasibility of accurately detecting moderate-severe sleep apnea early in the stroke recovery process using wearable sensors and machine learning techniques. These findings can inform future efforts to improve early detection for post-stroke sleep disorders, thereby enhancing patient recovery and long-term outcomes.

Validity and reliability study of a novel surface electromyography sensor using a well-consolidated electromyography system in individuals with cervical spinal cord injury.

STUDY DESIGN: Non-interventional, cross-sectional pilot study. OBJECTIVES: To establish the validity and reliability of the BioStamp nPoint biosensor (Medidata Solutions, New York, NY, USA [formerly MC10, Inc.]) for measuring electromyography in individuals with cervical spinal cord injury (SCI) by comparing the surface electromyography (sEMG) metrics with the Trigno wireless electromyography system (Delsys, Natick, MA, USA). SETTING: Participants were recruited from the Shirley Ryan AbilityLab registry. METHODS: Individuals aged 18-70 years with cervical SCI were evaluated with the two biosensors to capture activity on upper-extremity muscles during two study sessions conducted over 2 days (day 1-consent alone; day 2-two data collections in same session). Time and frequency metrics were captured, and signal-to-noise ratio was determined for each muscle group. Test-retest reliability was determined using Pearson's correlation. Validation of the BioStamp nPoint system was based on Bland-Altmann analysis. RESULTS: Among the 11 participants, 30.8% had subacute cervical injury at C5-C6; 53.8% were injured within 1 year of the study. Results from the test-retest reliability assessment revealed that most Pearson's correlations between the two sensory measurements were strong (≥0.50). The Bland-Altman analysis found values of the signal-to-noise ratio, frequency, and peak amplitude were within the level of agreement. Signal-to-noise ratios ranged from 7.06 to 22.1. CONCLUSIONS: In most instances, the performance of the BioStamp nPoint sensors was moderately to strongly correlated with that of the Trigno sensors in all muscle groups tested. The BioStamp nPoint system is a valid and reliable approach to assess sEMG measures in individuals with cervical SCI. SPONSORSHIP: The present study was supported by AbbVie Inc.

Noninvasive spinal stimulation improves walking in chronic stroke survivors: a proof-of-concept case series.

BACKGROUND: After stroke, restoring safe, independent, and efficient walking is a top rehabilitation priority. However, in nearly 70% of stroke survivors asymmetrical walking patterns and reduced walking speed persist. This case series study aims to investigate the effectiveness of transcutaneous spinal cord stimulation (tSCS) in enhancing walking ability of persons with chronic stroke. METHODS: Eight participants with hemiparesis after a single, chronic stroke were enrolled. Each participant was assigned to either the Stim group (N = 4, gait training + tSCS) or Control group (N = 4, gait training alone). Each participant in the Stim group was matched to a participant in the Control group based on age, time since stroke, and self-selected gait speed. For the Stim group, tSCS was delivered during gait training via electrodes placed on the skin between the spinous processes of C5-C6, T11-T12, and L1-L2. Both groups received 24 sessions of gait training over 8 weeks with a physical therapist providing verbal cueing for improved gait symmetry. Gait speed (measured from 10 m walk test), endurance (measured from 6 min walk test), spatiotemporal gait symmetries (step length and swing time), as well as the neurophysiological outcomes (muscle synergy, resting motor thresholds via spinal motor evoked responses) were collected without tSCS at baseline, completion, and 3 month follow-up. RESULTS: All four Stim participants sustained spatiotemporal symmetry improvements at the 3 month follow-up (step length: 17.7%, swing time: 10.1%) compared to the Control group (step length: 1.1%, swing time 3.6%). Additionally, 3 of 4 Stim participants showed increased number of muscle synergies and/or lowered resting motor thresholds compared to the Control group. CONCLUSIONS: This study provides promising preliminary evidence that using tSCS as a therapeutic catalyst to gait training may increase the efficacy of gait rehabilitation in individuals with chronic stroke. Trial registration NCT03714282 (clinicaltrials.gov), registration date: 2018-10-18.

Efficacy and safety of using auditory-motor entrainment to improve walking after stroke: a multi-site randomized controlled trial of InTandemTM.

Walking slowly after stroke reduces health and quality of life. This multi-site, prospective, interventional, 2-arm randomized controlled trial (NCT04121754) evaluated the safety and efficacy of an autonomous neurorehabilitation system (InTandemTM) designed to use auditory-motor entrainment to improve post-stroke walking. 87 individuals were randomized to 5-week walking interventions with InTandem or Active Control (i.e., walking without InTandem). The primary endpoints were change in walking speed, measured by the 10-meter walk test pre-vs-post each 5-week intervention, and safety, measured as the frequency of adverse events (AEs). Clinical responder rates were also compared. The trial met its primary endpoints. InTandem was associated with a 2x larger increase in speed (Δ: 0.14 ± 0.03 m/s versus Δ: 0.06 ± 0.02 m/s, F(1,49) = 6.58, p = 0.013), 3x more responders (40% versus 13%, χ2(1) ≥ 6.47, p = 0.01), and similar safety (both groups experienced the same number of AEs). The auditory-motor intervention autonomously delivered by InTandem is safe and effective in improving walking in the chronic phase of stroke.

Early Prediction of Poststroke Rehabilitation Outcomes Using Wearable Sensors.

OBJECTIVE: Inpatient rehabilitation represents a critical setting for stroke treatment, providing intensive, targeted therapy and task-specific practice to minimize a patient's functional deficits and facilitate their reintegration into the community. However, impairment and recovery vary greatly after stroke, making it difficult to predict a patient's future outcomes or response to treatment. In this study, the authors examined the value of early-stage wearable sensor data to predict 3 functional outcomes (ambulation, independence, and risk of falling) at rehabilitation discharge. METHODS: Fifty-five individuals undergoing inpatient stroke rehabilitation participated in this study. Supervised machine learning classifiers were retrospectively trained to predict discharge outcomes using data collected at hospital admission, including patient information, functional assessment scores, and inertial sensor data from the lower limbs during gait and/or balance tasks. Model performance was compared across different data combinations and was benchmarked against a traditional model trained without sensor data. RESULTS: For patients who were ambulatory at admission, sensor data improved the predictions of ambulation and risk of falling (with weighted F1 scores increasing by 19.6% and 23.4%, respectively) and maintained similar performance for predictions of independence, compared to a benchmark model without sensor data. The best-performing sensor-based models predicted discharge ambulation (community vs household), independence (high vs low), and risk of falling (normal vs high) with accuracies of 84.4%, 68.8%, and 65.9%, respectively. Most misclassifications occurred with admission or discharge scores near the classification boundary. For patients who were nonambulatory at admission, sensor data recorded during simple balance tasks did not offer predictive value over the benchmark models. CONCLUSION: These findings support the continued investigation of wearable sensors as an accessible, easy-to-use tool to predict the functional recovery after stroke. IMPACT: Accurate, early prediction of poststroke rehabilitation outcomes from wearable sensors would improve our ability to deliver personalized, effective care and discharge planning in the inpatient setting and beyond.

Circulating T cell specific extracellular vesicle profiles in cardiac allograft acute cellular rejection.

There is a critical need for biomarkers of acute cellular rejection (ACR) in organ transplantation. We hypothesized that ACR leads to changes in donor-reactive T cell small extracellular vesicle (sEV) profiles in transplant recipient circulation that match the kinetics of alloreactive T cell activation. In rodent heart transplantation, circulating T cell sEV quantities (P < .0001) and their protein and mRNA cargoes showed time-specific expression of alloreactive and regulatory markers heralding early ACR in allogeneic transplant recipients but not in syngeneic transplant recipients. Next generation sequencing of their microRNA cargoes identified novel candidate biomarkers of ACR, which were validated by stem loop quantitative reverse transcription polymerase chain reaction (n = 10). Circulating T cell sEVs enriched from allogeneic transplant recipients mediated targeted cytotoxicity of donor cardiomyocytes by apoptosis assay (P < .0001). Translation of the concept and EV methodologies to clinical heart transplantation demonstrated similar upregulation of circulating T cell sEV profiles at time points of grade 2 ACR (n = 3 patients). Furthermore, T cell receptor sequencing of T cell sEV mRNA cargo demonstrated expression of T cell clones with intact complementarity determining region 3 signals. These data support the diagnostic potential of T cell sEVs as noninvasive biomarker of ACR and suggest their potential functional roles.

Validation of Proprietary and Novel Step-counting Algorithms for Individuals Ambulating With a Lower Limb Prosthesis.

OBJECTIVE: To compare the accuracy and reliability of 10 different accelerometer-based step-counting algorithms for individuals with lower limb loss, accounting for different clinical characteristics and real-world activities. DESIGN: Cross-sectional study. SETTING: General community setting (ie, institutional research laboratory and community free-living). PARTICIPANTS: Forty-eight individuals with a lower limb amputation (N=48) wore an ActiGraph (AG) wGT3x-BT accelerometer proximal to the foot of their prosthetic limb during labeled indoor/outdoor activities and community free-living. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Intraclass correlation coefficient (ICC), absolute and root mean square error (RMSE), and Bland Altman plots were used to compare true (manual) step counts to estimated step counts from the proprietary AG Default algorithm and low frequency extension filter, as well as from 8 novel algorithms based on continuous wavelet transforms, fast Fourier transforms (FFTs), and peak detection. RESULTS: All algorithms had excellent agreement with manual step counts (ICC>0.9). The AG Default and FFT algorithms had the highest overall error (RMSE=17.81 and 19.91 steps, respectively), widest limits of agreement, and highest error during outdoor and ramp ambulation. The AG Default algorithm also had among the highest error during indoor ambulation and stairs, while a FFT algorithm had the highest error during stationary tasks. Peak detection algorithms, especially those using pre-set parameters with a trial-specific component, had among the lowest error across all activities (RMSE=4.07-8.99 steps). CONCLUSIONS: Because of its simplicity and accuracy across activities and clinical characteristics, we recommend the peak detection algorithm with set parameters to count steps using a prosthetic-worn AG among individuals with lower limb loss for clinical and research applications.

AI in Rehabilitation Medicine: Opportunities and Challenges.

Artificial intelligence (AI) tools are increasingly able to learn from larger and more complex data, thus allowing clinicians and scientists to gain new insights from the information they collect about their patients every day. In rehabilitation medicine, AI can be used to find patterns in huge amounts of healthcare data. These patterns can then be leveraged at the individual level, to design personalized care strategies and interventions to optimize each patient's outcomes. However, building effective AI tools requires many careful considerations about how we collect and handle data, how we train the models, and how we interpret results. In this perspective, we discuss some of the current opportunities and challenges for AI in rehabilitation. We first review recent trends in AI for the screening, diagnosis, treatment, and continuous monitoring of disease or injury, with a special focus on the different types of healthcare data used for these applications. We then examine potential barriers to designing and integrating AI into the clinical workflow, and we propose an end-to-end framework to address these barriers and guide the development of effective AI for rehabilitation. Finally, we present ideas for future work to pave the way for AI implementation in real-world rehabilitation practices.

A Research Protocol to Study the Priming Effects of Breathing Low Oxygen on Enhancing Training-Related Gains in Walking Function for Persons With Spinal Cord Injury: The BO2ST Trial.

Brief episodes of low oxygen breathing (therapeutic acute intermittent hypoxia; tAIH) may serve as an effective plasticity-promoting primer to enhance the effects of transcutaneous spinal stimulation-enhanced walking therapy (WALKtSTIM) in persons with chronic (>1 year) spinal cord injury (SCI). Pre-clinical studies in rodents with SCI show that tAIH and WALKtSTIM therapies harness complementary mechanisms of plasticity to maximize walking recovery. Here, we present a multi-site clinical trial protocol designed to examine the influence of tAIH + WALKtSTIM on walking recovery in persons with chronic SCI. We hypothesize that daily (eight sessions, 2 weeks) tAIH + WALKtSTIM will elicit faster, more persistent improvements in walking recovery than either treatment alone. To test our hypothesis, we are conducting a placebo-controlled clinical trial on 60 SCI participants who randomly receive one of three interventions: tAIH + WALKtSTIM; Placebo + WALKtSTIM; and tAIH + WALKtSHAM. Participants receive daily tAIH (fifteen 90-sec episodes at 10% O2 with 60-sec intervals at 21% O2) or daily placebo (fifteen 90-sec episodes at 21% O2 with 60-sec intervals at 21% O2) before a 45-min session of WALKtSTIM or WALKtSHAM. Our primary outcome measures assess walking speed (10-Meter Walk Test), endurance (6-Minute Walk Test), and balance (Timed Up and Go Test). For safety, we also measure pain levels, spasticity, sleep behavior, cognition, and rates of systemic hypertension and autonomic dysreflexia. Assessments occur before, during, and after sessions, as well as at 1, 4, and 8 weeks post-intervention. Results from this study extend our understanding of the functional benefits of tAIH priming by investigating its capacity to boost the neuromodulatory effects of transcutaneous spinal stimulation on restoring walking after SCI. Given that there is no known cure for SCI and no single treatment is sufficient to overcome walking deficits, there is a critical need for combinatorial treatments that accelerate and anchor walking gains in persons with lifelong SCI. Trial Registration: ClinicalTrials.gov, NCT05563103.

Evaluation of a carepartner-integrated telehealth gait rehabilitation program for persons with stroke: study protocol for a feasibility study.

BACKGROUND: Despite family carepartners of individuals post-stroke experiencing high levels of strain and reduced quality of life, stroke rehabilitation interventions rarely address carepartner well-being or offer training to support their engagement in therapeutic activities. Our group has developed creative intervention approaches to support families during stroke recovery, thereby improving physical and psychosocial outcomes for both carepartners and stroke survivors. The purpose of this study is to test the feasibility of an adapted, home-based intervention (Carepartner Collaborative Integrative Therapy for Gait-CARE-CITE-Gait) designed to facilitate positive carepartner involvement during home-based training targeting gait and mobility. METHODS: This two-phased design will determine the feasibility of CARE-CITE-Gait, a novel intervention that leverages principles from our previous carepartner-focused upper extremity intervention. During the 4-week CARE-CITE-Gait intervention, carepartners review online video-based modules designed to illustrate strategies for an autonomy-supportive environment during functional mobility task practice, and the study team completes two 2-h home visits for dyad collaborative goal setting. In phase I, content validity, usability, and acceptability of the CARE-CITE-Gait modules will be evaluated by stroke rehabilitation content experts and carepartners. In phase II, feasibility (based on measures of recruitment, retention, intervention adherence, and safety) will be measured. Preliminary effects of the CARE-CITE-Gait will be gathered using a single-group, quasi-experimental design with repeated measures (two baseline visits 1 week apart, posttest, and 1-month follow-up) with 15 carepartner and stroke survivor dyads. Outcome data collectors will be blinded. Outcomes include psychosocial variables (family conflict surrounding stroke recovery, strain, autonomy support, and quality of life) collected from carepartners and measures of functional mobility, gait speed, stepping activity, and health-related quality of life collected from stroke survivors. DISCUSSION: The findings of the feasibility testing and preliminary data on the effects of CARE-CITE-Gait will provide justification and information to guide a future definitive randomized clinical trial. The knowledge gained from this study will enhance our understanding of and aid the development of rehabilitation approaches that address both carepartner and stroke survivor needs during the stroke recovery process. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05257928. Registered 25 February 2022. TRIAL STATUS: This trial was registered on ClinicalTrials.gov (NCT05257928) on March 25, 2022. Recruitment of participants was initiated on May 18, 2022.

Protocol for a randomized controlled trial to evaluate a year-long (NICU-to-home) evidence-based, high dose physical therapy intervention in infants at risk of neuromotor delay.

INTRODUCTION: Developmental disabilities and neuromotor delay adversely affect long-term neuromuscular function and quality of life. Current evidence suggests that early therapeutic intervention reduces the severity of motor delay by harnessing neuroplastic potential during infancy. To date, most early therapeutic intervention trials are of limited duration and do not begin soon after birth and thus do not take full advantage of early neuroplasticity. The Corbett Ryan-Northwestern-Shirley Ryan AbilityLab-Lurie Children's Infant Early Detection, Intervention and Prevention Project (Project Corbett Ryan) is a multi-site longitudinal randomized controlled trial to evaluate the efficacy of an evidence-based physical therapy intervention initiated in the neonatal intensive care unit (NICU) and continuing to 12 months of age (corrected when applicable). The study integrates five key principles: active learning, environmental enrichment, caregiver engagement, a strengths-based approach, and high dosage (ClinicalTrials.gov identifier NCT05568264). METHODS: We will recruit 192 infants at risk for neuromotor delay who were admitted to the NICU. Infants will be randomized to either a standard-of-care group or an intervention group; infants in both groups will have access to standard-of-care services. The intervention is initiated in the NICU and continues in the infant's home until 12 months of age. Participants will receive twice-weekly physical therapy sessions and caregiver-guided daily activities, assigned by the therapist, targeting collaboratively identified goals. We will use various standardized clinical assessments (General Movement Assessment; Bayley Scales of Infant and Toddler Development, 4th Edition (Bayley-4); Test of Infant Motor Performance; Pediatric Quality of Life Inventory Family Impact Module; Alberta Infant Motor Scale; Neurological, Sensory, Motor, Developmental Assessment; Hammersmith Infant Neurological Examination) as well as novel technology-based tools (wearable sensors, video-based pose estimation) to evaluate neuromotor status and development throughout the course of the study. The primary outcome is the Bayley-4 motor score at 12 months; we will compare scores in infants receiving the intervention vs. standard-of-care therapy.

Understanding corticomotor mechanisms for activation of non-target muscles during unilateral isometric contractions of leg muscles after stroke.

PURPOSE: Muscle activation often occurs in muscles ipsilateral to a voluntarily activated muscle and to a greater extent after stroke. In this study, we measured muscle activation in non-target, ipsilateral leg muscles and used transcranial magnetic stimulation (TMS) to provide insight into whether corticomotor pathways contribute to involuntary activation. MATERIALS AND METHODS: Individuals with stroke performed unilateral isometric ankle dorsiflexion, ankle plantarflexion, knee extension, and knee flexion. To quantify involuntary muscle activation in non-target muscles, muscle activation was measured during contractions from the ipsilateral tibialis anterior (TA), medial gastrocnemius (MG), rectus femoris (RF), and biceps femoris (BF) and normalized to resting muscle activity. To provide insight into mechanisms of involuntary non-target muscle activation, TMS was applied to the contralateral hemisphere, and motor evoked potentials (MEPs) were recorded. RESULTS: We found significant muscle activation in nearly every non-target muscle during isometric unilateral contractions. MEPs were frequently observed in non-target muscles, but greater non-target MEP amplitude was not associated with greater non-target muscle activation. CONCLUSIONS: Our results suggest that non-target muscle activation occurs frequently in individuals with chronic stroke. The lack of association between non-target TMS responses and non-target muscle activation suggests that non-target muscle activation may have a subcortical or spinal origin. Non-target muscle activation has important clinical implications because it may impair torque production, out-of-synergy movement, and muscle activation timing.