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.

Modular hip exoskeleton improves walking function and reduces sedentary time in community-dwelling older adults.

BACKGROUND: Despite the benefits of physical activity for healthy physical and cognitive aging, 35% of adults over the age of 75 in the United States are inactive. Robotic exoskeleton-based exercise studies have shown benefits in improving walking function, but most are conducted in clinical settings with a neurologically impaired population. Emerging technology is starting to enable easy-to-use, lightweight, wearable robots, but their impact in the otherwise healthy older adult population remains mostly unknown. For the first time, this study investigates the feasibility and efficacy of using a lightweight, modular hip exoskeleton for in-community gait training in the older adult population to improve walking function. METHODS: Twelve adults over the age of 65 were enrolled in a gait training intervention involving twelve 30-min sessions using the Gait Enhancing and Motivating System for Hip in their own senior living community. RESULTS: Performance-based outcome measures suggest clinically significant improvements in balance, gait speed, and endurance following the exoskeleton training, and the device was safe and well tolerated. Gait speed below 1.0 m/s is an indicator of fall risk, and two out of the four participants below this threshold increased their self-selected gait speed over 1.0 m/s after intervention. Time spent in sedentary behavior also decreased significantly. CONCLUSIONS: This intervention resulted in greater improvements in speed and endurance than traditional exercise programs, in significantly less time. Together, our results demonstrated that exoskeleton-based gait training is an effective intervention and novel approach to encouraging older adults to exercise and reduce sedentary time, while improving walking function. Future work will focus on whether the device can be used independently long-term by older adults as an everyday exercise and community-use personal mobility device. Trial registration This study was retrospectively registered with ClinicalTrials.gov (ID: NCT05197127).

Autoencoder Composite Scoring to Evaluate Prosthetic Performance in Individuals with Lower Limb Amputation.

We created an overall assessment metric using a deep learning autoencoder to directly compare clinical outcomes in a comparison of lower limb amputees using two different prosthetic devices­a mechanical knee and a microprocessor-controlled knee. Eight clinical outcomes were distilled into a single metric using a seven-layer deep autoencoder, with the developed metric compared to similar results from principal component analysis (PCA). The proposed methods were used on data collected from ten participants with a dysvascular transfemoral amputation recruited for a prosthetics research study. This single summary metric permitted a cross-validated reconstruction of all eight scores, accounting for 83.29% of the variance. The derived score is also linked to the overall functional ability in this limited trial population, as improvements in each base clinical score led to increases in this developed metric. There was a highly significant increase in this autoencoder-based metric when the subjects used the microprocessor-controlled knee (p < 0.001, repeated measures ANOVA). A traditional PCA metric led to a similar interpretation but captured only 67.3% of the variance. The autoencoder composite score represents a single-valued, succinct summary that can be useful for the holistic assessment of highly variable, individual scores in limited clinical datasets.

Wearable airbag technology and machine learned models to mitigate falls after stroke.

BACKGROUND: Falls are a common complication experienced after a stroke and can cause serious detriments to physical health and social mobility, necessitating a dire need for intervention. Among recent advancements, wearable airbag technology has been designed to detect and mitigate fall impact. However, these devices have not been designed nor validated for the stroke population and thus, may inadequately detect falls in individuals with stroke-related motor impairments. To address this gap, we investigated whether population-specific training data and modeling parameters are required to pre-detect falls in a chronic stroke population. METHODS: We collected data from a wearable airbag's inertial measurement units (IMUs) from individuals with (n = 20 stroke) and without (n = 15 control) history of stroke while performing a series of falls (842 falls total) and non-falls (961 non-falls total) in a laboratory setting. A leave-one-subject-out crossvalidation was used to compare the performance of two identical machine learned models (adaptive boosting classifier) trained on cohort-dependent data (control or stroke) to pre-detect falls in the stroke cohort. RESULTS: The average performance of the model trained on stroke data (recall = 0.905, precision = 0.900) had statistically significantly better recall (P = 0.0035) than the model trained on control data (recall = 0.800, precision = 0.944), while precision was not statistically significantly different. Stratifying models trained on specific fall types revealed differences in pre-detecting anterior-posterior (AP) falls (stroke-trained model's F1-score was 35% higher, P = 0.019). Using activities of daily living as non-falls training data (compared to near-falls) significantly increased the AUC (Area under the receiver operating characteristic) for classifying AP falls for both models (P < 0.04). Preliminary analysis suggests that users with more severe stroke impairments benefit further from a stroke-trained model. The optimal lead time (time interval pre-impact to detect falls) differed between control- and stroke-trained models. CONCLUSIONS: These results demonstrate the importance of population sensitivity, non-falls data, and optimal lead time for machine learned pre-impact fall detection specific to stroke. Existing fall mitigation technologies should be challenged to include data of neurologically impaired individuals in model development to adequately detect falls in other high fall risk populations. Trial registration https://clinicaltrials.gov/ct2/show/NCT05076565 ; Unique Identifier: NCT05076565. Retrospectively registered on 13 October 2021.

Predicting Duration of Outpatient Physical Therapy Episodes for Individuals with Spinal Cord Injury Based on Locomotor Training Strategy.

OBJECTIVE: To characterize individuals with spinal cord injuries (SCI) who use outpatient physical therapy or community wellness services for locomotor training and predict the duration of services, controlling for demographic, injury, quality of life, and service and financial characteristics. We explore how the duration of services is related to locomotor strategy. DESIGN: Observational study of participants at 4 SCI Model Systems centers with survival. Weibull regression model to predict the duration of services. SETTING: Rehabilitation and community wellness facilities at 4 SCI Model Systems centers. PARTICIPANTS: Eligibility criteria were SCI or dysfunction resulting in motor impairment and the use of physical therapy or community wellness programs for locomotor/gait training. We excluded those who did not complete training or who experienced a disruption in training greater than 45 days. Our sample included 62 participants in conventional therapy and 37 participants in robotic exoskeleton training. INTERVENTIONS: Outpatient physical therapy or community wellness services for locomotor/gait training. MAIN OUTCOME MEASURES: SCI characteristics (level and completeness of injury) and the duration of services from medical records. Self-reported perceptions of SCI consequences using the SCI-Functional Index for basic mobility and SCI-Quality of Life measurement system for bowel difficulties, bladder difficulties, and pain interference. RESULTS: After controlling for predictors, the duration of services for the conventional therapy group was an average of 63% longer than for the robotic exoskeleton group, however each visit was 50% shorter in total time. Men had an 11% longer duration of services than women had. Participants with complete injuries had a duration of services that was approximately 1.72 times longer than participants with incomplete injuries. Perceived improvement was larger in the conventional group. CONCLUSIONS: Locomotor/gait training strategies are distinctive for individuals with SCI using a robotic exoskeleton in a community wellness facility as episodes are shorter but individual sessions are longer. Participants' preferences and the ability to pay for ongoing services may be critical factors associated with the duration of outpatient services.

Usability, functionality, and efficacy of a custom myoelectric elbow-wrist-hand orthosis to assist elbow function in individuals with stroke.

INTRODUCTION: After stroke, upper limb impairment affects independent performance of activities of daily living. We evaluated the usability, functionality, and efficacy of a myoelectric elbow-wrist-hand orthosis to provide support, limit unsafe motion, and enhance the functional motion of paralyzed or weak upper limbs. METHODS: Individuals with stroke participated in a single-session study to evaluate the device. Ability to activate the device was tested in supported and unsupported shoulder position, as well as the elbow range of motion, ability to maintain elbow position, and ability to lift and hold a range of weights while using the device. RESULTS: No adverse events were reported. 71% of users were able to operate the device in all three active myoelectric activation modes (Biceps, Triceps, Dual) during testing. Users were able to hold a range of wrist weights (0.5-2 lbs) for 10-120 seconds, with the largest percentage of participants able to hold weights with the device in Biceps Mode. CONCLUSIONS: The myoelectric elbow-wrist-hand orthosis improved range of motion during use and was efficacious at remediating upper extremity impairment after stroke. All users could operate the device in at least one mode, and most could lift and hold weights representative of some everyday objects using the device.

A smartphone-based online system for fall detection with alert notifications and contextual information of real-life falls.

BACKGROUND: Falls are a leading cause of accidental deaths and injuries worldwide. The risk of falling is especially high for individuals suffering from balance impairments. Retrospective surveys and studies of simulated falling in lab conditions are frequently used and are informative, but prospective information about real-life falls remains sparse. Such data are essential to address fall risks and develop fall detection and alert systems. Here we present the results of a prospective study investigating a proof-of-concept, smartphone-based, online system for fall detection and notification. METHODS: The system uses the smartphone's accelerometer and gyroscope to monitor the participants' motion, and falls are detected using a regularized logistic regression. Data on falls and near-fall events (i.e., stumbles) is stored in a cloud server and fall-related variables are logged onto a web portal developed for data exploration, including the event time and weather, fall probability, and the faller's location and activity before the fall. RESULTS: In total, 23 individuals with an elevated risk of falling carried the phones for 2070 days in which the model classified 14,904,000 events. The system detected 27 of the 37 falls that occurred (sensitivity = 73.0 %) and resulted in one false alarm every 46 days (specificity > 99.9 %, precision = 37.5 %). 42.2 % of the events falsely classified as falls were validated as stumbles. CONCLUSIONS: The system's performance shows the potential of using smartphones for fall detection and notification in real-life. Apart from functioning as a practical fall monitoring instrument, this system may serve as a valuable research tool, enable future studies to scale their ability to capture fall-related data, and help researchers and clinicians to investigate real-falls.

Combining Accelerometer and GPS Features to Evaluate Community Mobility in Knee Ankle Foot Orthoses (KAFO) Users.

Orthotic and assistive devices such as knee ankle foot orthoses (KAFO), come in a variety of forms and fits, with several levels of available features that could help users perform daily activities more naturally. However, objective data on the actual use of these devices outside of the research lab is usually not obtained. Such data could enhance traditional lab-based outcome measures and inform clinical decision-making when prescribing new orthotic and assistive technology. Here, we link data from a GPS unit and an accelerometer mounted on the orthotic device to quantify its usage in the community and examine the correlations with clinical metrics. We collected data from 14 individuals over a period of 2 months as they used their personal KAFO first, and then a novel research KAFO; for each device we quantified number of steps, cadence, time spent at community locations and time wearing the KAFO at those locations. Sensor-derived metrics showed that mobility patterns differed widely between participants (mean steps: 591.3, SD =704.2). The novel KAFO generally enabled participants to walk faster during clinical tests ( ∆6 Minute-Walk-Test=71.5m, p=0.006). However, some participants wore the novel device less often despite improved performance on these clinical measures, leading to poor correlation between changes in clinical outcome measures and changes in community mobility ( ∆6 Minute-Walk-Test - ∆ Community Steps: r=0.09, p=0.76). Our results suggest that some traditional clinical outcome measures may not be associated with the actual wear time of an assistive device in the community, and obtaining personalized data from real-world use through wearable technology is valuable.

Using a microprocessor knee (C-Leg) with appropriate foot transitioned individuals with dysvascular transfemoral amputations to higher performance levels: a longitudinal randomized clinical trial.

BACKGROUND: Individuals with transfemoral amputations who are considered to be limited community ambulators are classified as Medicare functional classification (MFCL) level K2. These individuals are usually prescribed a non-microprocessor controlled knee (NMPK) with an appropriate foot for simple walking functions. However, existing research suggests that these individuals can benefit from using a microprocessor controlled knee (MPK) and appropriate foot for their ambulation, but cannot obtain one due to insurance policy restrictions. With a steady increase in older adults with amputations due to vascular conditions, it is critical to evaluate whether advanced prostheses can provide better safety and performance capabilities to maintain and improve quality of life in individuals who are predominantly designated MFCL level K2. To decipher this we conducted a 13 month longitudinal clinical trial to determine the benefits of using a C-Leg and 1M10 foot in individuals at K2 level with transfemoral amputation due to vascular disease. This longitudinal clinical trial incorporated recommendations prescribed by the lower limb prosthesis workgroup to design a study that can add evidence to improve reimbursement policy through clinical outcomes using an MPK in K2 level individuals with transfemoral amputation who were using an NMPK for everyday use. METHODS: Ten individuals (mean age: 63 ± 9 years) with unilateral transfemoral amputation due to vascular conditions designated as MFCL K2 participated in this longitudinal crossover randomized clinical trial. Baseline outcomes were collected with their current prosthesis. Participants were then randomized to one of two groups, either an intervention with the MPK with a standardized 1M10 foot or their predicate NMPK with a standardized 1M10 foot. On completion of the first intervention, participants crossed over to the next group to complete the study. Each intervention lasted for 6 months (3 months of acclimation and 3 months of take-home trial to monitor home use). At the end of each intervention, clinical outcomes and self-reported outcomes were collected to compare with their baseline performance. A generalized linear model ANOVA was used to compare the performance of each intervention with respect to their own baseline. RESULTS: Statistically significant and clinically meaningful improvements were observed in gait performance, safety, and participant-reported measures when using the MPK C-Leg + 1M10 foot. Most participants were able to achieve higher clinical scores in gait speed, balance, self-reported mobility, and fall safety, while using the MPK + 1M10 combination. The improvement in scores were within range of scores achieved by individuals with K3 functional level as reported in previous studies. CONCLUSIONS: Individuals with transfemoral amputation from dysvascular conditions designated MFCL level K2 benefited from using an MPK + appropriate foot. The inference and evidence from this longitudinal clinical trial will add to the knowledgebase related to reimbursement policy-making. Trial registration This study is registered on clinical trials.gov with the study title "Functional outcomes in dysvascular transfemoral amputees" and the associated ClinicalTrials.gov Identifier: NCT01537211. The trial was retroactively registered on February 7, 2012 after the first participant was enrolled.

Differential cardiopulmonary monitoring system for artifact-canceled physiological tracking of athletes, workers, and COVID-19 patients.

Soft, skin-integrated electronic sensors can provide continuous measurements of diverse physiological parameters, with broad relevance to the future of human health care. Motion artifacts can, however, corrupt the recorded signals, particularly those associated with mechanical signatures of cardiopulmonary processes. Design strategies introduced here address this limitation through differential operation of a matched, time-synchronized pair of high-bandwidth accelerometers located on parts of the anatomy that exhibit strong spatial gradients in motion characteristics. When mounted at a location that spans the suprasternal notch and the sternal manubrium, these dual-sensing devices allow measurements of heart rate and sounds, respiratory activities, body temperature, body orientation, and activity level, along with swallowing, coughing, talking, and related processes, without sensitivity to ambient conditions during routine daily activities, vigorous exercises, intense manual labor, and even swimming. Deployments on patients with COVID-19 allow clinical-grade ambulatory monitoring of the key symptoms of the disease even during rehabilitation protocols.

Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients.

Capabilities in continuous monitoring of key physiological parameters of disease have never been more important than in the context of the global COVID-19 pandemic. Soft, skin-mounted electronics that incorporate high-bandwidth, miniaturized motion sensors enable digital, wireless measurements of mechanoacoustic (MA) signatures of both core vital signs (heart rate, respiratory rate, and temperature) and underexplored biomarkers (coughing count) with high fidelity and immunity to ambient noises. This paper summarizes an effort that integrates such MA sensors with a cloud data infrastructure and a set of analytics approaches based on digital filtering and convolutional neural networks for monitoring of COVID-19 infections in sick and healthy individuals in the hospital and the home. Unique features are in quantitative measurements of coughing and other vocal events, as indicators of both disease and infectiousness. Systematic imaging studies demonstrate correlations between the time and intensity of coughing, speaking, and laughing and the total droplet production, as an approximate indicator of the probability for disease spread. The sensors, deployed on COVID-19 patients along with healthy controls in both inpatient and home settings, record coughing frequency and intensity continuously, along with a collection of other biometrics. The results indicate a decaying trend of coughing frequency and intensity through the course of disease recovery, but with wide variations across patient populations. The methodology creates opportunities to study patterns in biometrics across individuals and among different demographic groups.

Rapid Screening of Physiological Changes Associated With COVID-19 Using Soft-Wearables and Structured Activities: A Pilot Study.

OBJECTIVE: Controlling the spread of the COVID-19 pandemic largely depends on scaling up the testing infrastructure for identifying infected individuals. Consumer-grade wearables may present a solution to detect the presence of infections in the population, but the current paradigm requires collecting physiological data continuously and for long periods of time on each individual, which poses limitations in the context of rapid screening. Technology: Here, we propose a novel paradigm based on recording the physiological responses elicited by a short (~2 minutes) sequence of activities (i.e. "snapshot"), to detect symptoms associated with COVID-19. We employed a novel body-conforming soft wearable sensor placed on the suprasternal notch to capture data on physical activity, cardio-respiratory function, and cough sounds. RESULTS: We performed a pilot study in a cohort of individuals (n=14) who tested positive for COVID-19 and detected altered heart rate, respiration rate and heart rate variability, relative to a group of healthy individuals (n=14) with no known exposure. Logistic regression classifiers were trained on individual and combined sets of physiological features (heartbeat and respiration dynamics, walking cadence, and cough frequency spectrum) at discriminating COVID-positive participants from the healthy group. Combining features yielded an AUC of 0.94 (95% CI=[0.92, 0.96]) using a leave-one-subject-out cross validation scheme. Conclusions and Clinical Impact: These results, although preliminary, suggest that a sensor-based snapshot paradigm may be a promising approach for non-invasive and repeatable testing to alert individuals that need further screening.

Characterization of Motor-Evoked Responses Obtained with Transcutaneous Electrical Spinal Stimulation from the Lower-Limb Muscles after Stroke.

An increasing number of studies suggests that a novel neuromodulation technique targeting the spinal circuitry enhances gait rehabilitation, but research on its application to stroke survivors is limited. Therefore, we investigated the characteristics of spinal motor-evoked responses (sMERs) from lower-limb muscles obtained by transcutaneous spinal cord stimulation (tSCS) after stroke compared to age-matched and younger controls without stroke. Thirty participants (ten stroke survivors, ten age-matched controls, and ten younger controls) completed the study. By using tSCS applied between the L1 and L2 vertebral levels, we compared sMER characteristics (resting motor threshold (RMT), slope of the recruitment curve, and latency) of the tibialis anterior (TA) and medial gastrocnemius (MG) muscles among groups. A single pulse of stimulation was delivered in 5 mA increments, increasing from 5 mA to 250 mA or until the subjects reached their maximum tolerance. The stroke group had an increased RMT (27-51%) compared to both age-matched (TA: p = 0.032; MG: p = 0.005) and younger controls (TA: p < 0.001; MG: p<0.001). For the TA muscle, the paretic side demonstrated a 13% increased latency compared to the non-paretic side in the stroke group (p = 0.010). Age-matched controls also exhibited an increased RMT compared to younger controls (TA: p = 0.002; MG: p = 0.007), suggesting that altered sMER characteristics present in stroke survivors may result from both stroke and normal aging. This observation may provide implications for altered spinal motor output after stroke and demonstrates the feasibility of using sMER characteristics as an assessment after stroke.

Microprocessor Controlled Knee Ankle Foot Orthosis (KAFO) vs Stance Control vs Locked KAFO: A Randomized Controlled Trial.

OBJECTIVE: To evaluate the potential of a microprocessor swing and stance controlled knee-ankle-foot orthosis (MPO) to improve balance, functional mobility, and quality of life in individuals with lower-extremity impairments as compared to a stance-control-orthosis (SCO) and conventional knee-ankle-foot orthosis (KAFO) over a use-period of a month. DESIGN: Randomized crossover study. SETTING: Ambulatory research laboratory and home and community for community-dwelling adults. PARTICIPANTS: Persons (N=18) who actively used a unilateral KAFO or SCO for impairments due to neurologic or neuromuscular disease, orthopedic disease, or trauma. INTERVENTION: Participants were trained to acclimate and use SCO and MPO. MAIN OUTCOME MEASURES: The 6-minute walk test (6MWT), 10-m walk test, Berg Balance Scale (BBS), functional gait assessment (FGA), hill assessment index, stair assessment index (SAI), Five Times Sit to Stand Test, crosswalk test, Modified Falls Efficacy Scale, Orthotic and Prosthetic User's Survey (OPUS), and World Health Organization Quality of Life (WHQOL)-BREF Scale. RESULTS: Significant changes were observed in participants' self-selected gait speed (P=.023), BBS (P=.01), FGA (P=.002), and SAI (P<.001) between baseline and post-MPO assessment. Similar significant differences were seen when comparing post-MPO with post-SCO data. During the 6MWT, persons using the MPO walked significantly longer (P=.013) than when using their baseline device. Participants reported higher quality of life scores in the OPUS (P=.02) and physical health domain of the WHOQOL-BREF (P=.037) after using the MPO. Participants reported fewer falls when wearing the MPO (5) versus an SCO (38) or locked KAFO (15). CONCLUSIONS: The MPO may contribute to improved quality of life and health status of persons with lower-extremity impairments by providing the ability to have better walking speed, endurance, and functional balance.

Clinician Perceptions of Robotic Exoskeletons for Locomotor Training After Spinal Cord Injury: A Qualitative Approach.

OBJECTIVE: To describe the experiences of clinicians who have used robotic exoskeletons in their practice and acquire information that can guide clinical decisions and training strategies related to robotic exoskeletons. DESIGN: Qualitative, online survey study, and 4 single-session focus groups followed by thematic analysis to define themes. SETTING: Focus groups were conducted at 3 regional rehabilitation hospitals and 1 Veteran's Administration (VA) Medical Center. PARTICIPANTS: Clinicians (N=40) reported their demographic characteristics and clinical experience using robotic exoskeletons. Twenty-nine clinicians participated in focus groups at regional hospitals that use robotic exoskeletons, as well as 1 VA Medical Center. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Clinicians' preferences, experiences, training strategies, and clinical decisions on how robotic exoskeleton devices are used with Veterans and civilians with spinal cord injury. RESULTS: Clinicians had an average of 3 years of experience using exoskeletons in clinical and research settings. Major themes emerging from focus group discussions included appropriateness of patient goals, patient selection criteria, realistic patient expectations, patient and caregiver training for use of exoskeletons, perceived benefits, preferences regarding specific exoskeletons, and device limitations and therapy recommendations. CONCLUSIONS: Clinicians identified benefits of exoskeleton use including decreased physical burden and fatigue while maximizing patient mobility, increased safety of clinicians and patients, and expanded device awareness and preferences. Suitability of exoskeletons for patients with various characteristics and managing expectations were concerns. Clinicians identified research opportunities as technology continues to advance toward safer, lighter, and hands-free devices.

Users with spinal cord injury experience of robotic Locomotor exoskeletons: a qualitative study of the benefits, limitations, and recommendations.

BACKGROUND: Persons with spinal cord injury (SCI) may experience both psychological and physiological benefits from robotic locomotor exoskeleton use, and knowledgeable users may have valuable perspectives to inform future development. The objective of this study is to gain insight into the experiences, perspectives, concerns, and suggestions on the use of robotic locomotor exoskeletons by civilians and veterans living with SCI. METHODS: Participants reported their demographic characteristics and the extent of robotic exoskeleton use in an online survey. Then, 28 experienced robotic locomotor exoskeleton users participated in focus groups held at three regional hospitals that specialize in rehabilitation for persons with SCI. We used a qualitative description approach analysis to analyze the data, and included thematic analysis. RESULTS: Participants expressed that robotic exoskeletons were useful in therapy settings but, in their current form, were not practical for activities of daily living due to device limitations. Participants detailed the psychological benefits of being eye-level with their non-disabled peers and family members, and some reported physiologic improvements in areas such as bowel and bladder function. Participants detailed barriers of increased fatigue, spasticity, and spasms and expressed dissatisfaction with the devices due to an inability to use them independently and safely. Participants provided suggestions to manufacturers for technology improvements. CONCLUSIONS: The varied opinions and insights of robotic locomotor exoskeletons users with SCI add to our knowledge of device benefits and limitations.

The impact of a yoga-based physical therapy group for individuals with traumatic brain injury: results from a pilot study.

OBJECTIVE: To compare the impacts of yoga-based physical therapy versus a seated rest within the context of standard rehabilitation practice on sleep, heart rate variability (HRV), anxiety, and fatigue during acute traumatic brain injury (TBI) rehabilitation. METHODS: Eleven individuals participated in this crossover study involving the following interventions in a randomized order: group yoga-based physical therapy (YPT), conventional physical therapy (CPT), and group seated rest in a relaxing environment (SR). HRV and self-reported anxiety and fatigue were measured immediately before and after each group, and sleep after each condition and at baseline. Data was analyzed using generalized linear mixed models with repeated measures. RESULTS: The interaction between time and treatment was statistically significant (p = .0203). For the SR treatment, wake after sleep onset (WASO) rate was reduced from 14.99 to 10.60 (IRR = 0.71; p = .006). Time and treatment were not found to be statistically significantly associated with any of the secondary outcomes. CONCLUSION: Yoga-based physical therapy is feasible and safe in the inpatient rehabilitation setting following TBI. Sleep quality improved following the addition of a one-hour seated rest in a relaxing environment to a standard rehabilitation daily schedule, suggesting that structured rest time may be beneficial to sleep hygiene during inpatient rehabilitation following TBI. ClinicalTrials.Gov Registration Number: NCT03701594.

Appraisals of robotic locomotor exoskeletons for gait: focus group insights from potential users with spinal cord injuries.

Purpose: To describe appraisals of robotic exoskeletons for locomotion by potential users with spinal cord injuries, their perceptions of device benefits and limitations, and recommendations for manufacturers and therapists regarding device use.Materials and methods: We conducted focus groups at three regional rehabilitation hospitals and used thematic analysis to define themes.Results: Across four focus groups, 35 adults participated; they were predominantly middle-aged, male, and diverse in terms of race and ethnicity, well educated, and not working. Participants had been living with SCI an average of two decades. Most participants were aware of exoskeletons. Some were enthusiastic about the usability of the devices while others were more circumspect. They had many questions about device affordability and usability, and were discerning in their appraisal of benefits and suitability to their particular circumstances. They reflected on device cost, the need for caregiver assistance, use of hands, and environmental considerations. They weighed the functional benefits relative to the cost of preferred activities. Their recommendations focused on cost, battery life, and independent use.Conclusions: Potential users' appraisals of mobility technology reflect a nuanced appreciation of device costs; functional, social, and psychological benefits; and limitations. Results provide guidance to therapists and manufacturers regarding device use.Implications for RehabilitationPotential users of robotic locomotor exoskeletons with spinal cord injuries appreciate the functional, social, and psychological benefits that these devices may offer.Their appraisals reflect nuanced consideration of device cost and features, and the suitability of the assistive technology to their circumstances.They recommend that manufacturers focus on reducing cost, extending battery life, and features that allow independent use.

Budget impact analysis of robotic exoskeleton use for locomotor training following spinal cord injury in four SCI Model Systems.

BACKGROUND: We know little about the budget impact of integrating robotic exoskeleton over-ground training into therapy services for locomotor training. The purpose of this study was to estimate the budget impact of adding robotic exoskeleton over-ground training to existing locomotor training strategies in the rehabilitation of people with spinal cord injury. METHODS: A Budget Impact Analysis (BIA) was conducted using data provided by four Spinal Cord Injury (SCI) Model Systems rehabilitation hospitals. Hospitals provided estimates of therapy utilization and costs about people with spinal cord injury who participated in locomotor training in the calendar year 2017. Interventions were standard of care walking training including body-weight supported treadmill training, overground training, stationary robotic systems (i.e., treadmill-based robotic gait orthoses), and overground robotic exoskeleton training. The main outcome measures included device costs, training costs for personnel to use the device, human capital costs of locomotor training, device demand, and the number of training sessions per person with SCI. RESULTS: Robotic exoskeletons for over-ground training decreased hospital costs associated with delivering locomotor training in the base case analysis. This analysis assumed no difference in intervention effectiveness across locomotor training strategies. Providing robotic exoskeleton overground training for 10% of locomotor training sessions over the course of the year (range 226-397 sessions) results in decreased annual locomotor training costs (i.e., net savings) between $1114 to $4784 per annum. The base case shows small savings that are sensitive to parameters of the BIA model which were tested in one-way sensitivity analyses, scenarios analyses, and probability sensitivity analyses. The base case scenario was more sensitive to clinical utilization parameters (e.g., how often devices sit idle and the substitution of high cost training) than device-specific parameters (e.g., robotic exoskeleton device cost or device life). Probabilistic sensitivity analysis simultaneously considered human capital cost, device cost, and locomotor device substitution. With probabilistic sensitivity analysis, the introduction of a robotic exoskeleton only remained cost saving for one facility. CONCLUSIONS: Providing robotic exoskeleton for over-ground training was associated with lower costs for the locomotor training of people with SCI in the base case analyses. The analysis was sensitive to parameter assumptions.