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Relearning functional and symmetric walking after stroke using a wearable device: a feasibility study.

ABSTRACT: BACKGROUND:Gait impairment is a common consequence of stroke and typically involves a hemiparetic or asymmetric walking pattern. Asymmetric gait patterns are correlated with decreased gait velocity and efficiency as well as increased susceptibility to serious falls and injuries. RESEARCH QUESTION:This paper presents an innovative device worn on a foot for gait rehabilitation post stroke. The device generates a backward motion to the foot, which is designed to exaggerate the existing step length asymmetry while walking over ground. We hypothesize this motion will decrease gait asymmetry and improve functional walking in individuals with chronic stroke. METHODS:Six participants with chronic stroke, more than one year post stroke, received four weeks of gait training with three sessions per week. Each session included 30 min of walking over ground using the wearable device. Gait symmetry and functional walking were assessed before and after training. RESULTS:All participants improved step length symmetry, and four participants improved double limb support symmetry. All participants improved on all three functional outcomes (gait velocity, Timed Up and Go Test, and 6-Minute Walk Test), and five participants improved beyond the minimal detectable change or meaningful change in at least one functional outcome. CONCLUSION:The results indicate that the presented device may help improve stroke patients' walking ability and warrant further study. A gait training approach using this new device may enable and expand long-term continuous gait rehabilitation outside the clinic following stroke. TRIAL REGISTRATION:NCT02185404. Registered July 9, 2014, https://clinicaltrials.gov/ct2/show/NCT02185404.

SUBMITTER: Kim SH

PROVIDER: S-EPMC6712835 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Relearning functional and symmetric walking after stroke using a wearable device: a feasibility study.

Kim Seok Hun SH Huizenga David E DE Handzic Ismet I Ditwiler Rebecca Edgeworth RE Lazinski Matthew M Ramakrishnan Tyagi T Bozeman Andrea A Rose David Z DZ Reed Kyle B KB

Journal of neuroengineering and rehabilitation 20190828 1

<h4>Background</h4>Gait impairment is a common consequence of stroke and typically involves a hemiparetic or asymmetric walking pattern. Asymmetric gait patterns are correlated with decreased gait velocity and efficiency as well as increased susceptibility to serious falls and injuries.<h4>Research question</h4>This paper presents an innovative device worn on a foot for gait rehabilitation post stroke. The device generates a backward motion to the foot, which is designed to exaggerate the existi ...[more]

PMID: 31455358

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Project description:Humans routinely modify their walking speed to adapt to functional goals and physical demands. However, damage to the central nervous system (CNS) often results in abnormal modulation of walking speed and increased risk of falls. There is considerable interest in treatment modalities that can provide safe and salient training opportunities, feedback about walking performance, and that may augment less reliable sensory feedback within the CNS after injury or disease. Fully immersive virtual reality technologies show benefits in boosting training-related gains in walking performance; however, they lack views of the real world that may limit functional carryover. Augmented reality and mixed reality head-mount displays (MR-HMD) provide partially immersive environments to extend the virtual reality benefits of interacting with virtual objects but within an unobstructed view of the real world. Despite this potential advantage, the feasibility of using MR-HMD visual feedback to promote goal-directed changes in overground walking speed remains unclear. Thus, we developed and evaluated a novel mixed reality application using the Microsoft HoloLens MR-HMD that provided real-time walking speed targets and augmented visual feedback during overground walking. We tested the application in a group of adults not living with disability and examined if they could use the targets and visual feedback to walk at 85%, 100%, and 115% of each individual's self-selected speed. We examined whether individuals were able to meet each target gait speed and explored differences in accuracy across repeated trials and at the different speeds. Additionally, given the importance of task-specificity to therapeutic interventions, we examined if walking speed adjustment strategies were consistent with those observed during usual overground walking, and if walking with the MR-HMD resulted in increased variability in gait parameters. Overall, participants matched their overground walking speed to the target speed of the MR-HMD visual feedback conditions (all p-values > 0.05). The percent inaccuracy was approximately 5% across all speed matching conditions and remained consistent across walking trials after the first overall walking trial. Walking with the MR-HMD did not result in more variability in walking speed, however, we observed more variability in stride length and time when walking with feedback from the MR-HMD compared to walking without feedback. The findings offer support for mixed reality-based visual feedback as a method to provoke goal-specific changes in overground walking behavior. Further studies are necessary to determine the clinical safety and efficacy of this MR-HMD technology to provide extrinsic sensory feedback in combination with traditional treatments in rehabilitation.

Project description:BackgroundAdolescence is an important life stage for the development of healthy behaviors, which have a long-lasting impact on health across the lifespan. Sleep undergoes significant changes during adolescence and is linked to physical and psychiatric health; however, sleep is rarely assessed in routine health care settings. Wearable sleep electroencephalogram (EEG) devices may represent user-friendly methods for assessing sleep among adolescents, but no studies to date have examined the feasibility and acceptability of sleep EEG wearables in this age group.ObjectiveThe goal of the research was to investigate the feasibility and acceptability of sleep EEG wearable devices among adolescents aged 11 to 17 years.MethodsA total of 104 adolescents aged 11 to 17 years participated in 7 days of at-home sleep recording using a self-administered wearable sleep EEG device (Zmachine Insight+, General Sleep Corporation) as well as a wristworn actigraph. Feasibility was assessed as the number of full nights of successful recording completed by adolescents, and acceptability was measured by the wearable acceptability survey for sleep. Feasibility and acceptability were assessed separately for the sleep EEG device and wristworn actigraph.ResultsA total of 94.2% (98/104) of adolescents successfully recorded at least 1 night of data using the sleep EEG device (mean number of nights 5.42; SD 1.71; median 6, mode 7). A total of 81.6% (84/103) rated the comfort of the device as falling in the comfortable to mildly uncomfortable range while awake. A total of 40.8% (42/103) reported typical sleep while using the device, while 39.8% (41/103) indicated minimal to mild device-related sleep disturbances. A minority (32/104, 30.8%) indicated changes in their sleep position due to device use, and very few (11/103, 10.7%) expressed dissatisfaction with their experience with the device. A similar pattern was observed for the wristworn actigraph device.ConclusionsWearable sleep EEG appears to represent a feasible, acceptable method for sleep assessment among adolescents and may have utility for assessing and treating sleep disturbances at a population level. Future studies with adolescents should evaluate strategies for further improving usability of such devices, assess relationships between sleep EEG-derived metrics and health outcomes, and investigate methods for incorporating data from these devices into emerging digital interventions and applications.Trial registrationClinicalTrials.gov NCT03843762; https://clinicaltrials.gov/ct2/show/NCT03843762.

Project description:BackgroundContinuous tracking of ambulatory activity in real-world settings using step activity monitors has many potential uses. However, feasibility, accuracy, and correlation with performance measures in stroke patients have not been well-established.ObjectiveThe primary study objective was to determine adherence with wearing a consumer-grade step activity monitor, the Fitbit Charge HR, in home-going ischemic stroke patients during the first 90 days after hospital discharge. Secondary objectives were to (1) determine accuracy of step counts of the Fitbit Charge HR compared with a manual tally; (2) calculate correlations between the Fitbit step counts and the mobility performance scores at discharge and 30 days after stroke; (3) determine variability and change in weekly step counts over 90 days; and (4) evaluate patient experience with using the Fitbit Charge HR poststroke.MethodsA total of 15 participants with recent mild ischemic stroke wore a Fitbit Charge HR for 90 days after discharge and completed 3 mobility performance tests from the National Institutes of Health Toolbox at discharge and Day 30: (1) Standing Balance Test, (2) 2-Minute Walk Endurance Test, and (3) 4-Meter Walk Gait Speed Test. Accuracy of step activity monitors was assessed by calculating differences in steps recorded on the step activity monitor and a manual tally during 2-minute walk tests.ResultsParticipants had a mean age of 54 years and a median modified Rankin scale score of 1. Mean daily adherence with step activity monitor use was 83.6%. Mean daily step count in the first week after discharge was 4376. Daily step counts increased slightly during the first 30 days after discharge (average increase of 52.5 steps/day; 95% CI 32.2-71.8) and remained stable during the 30-90 day period after discharge. Mean step count difference between step activity monitor and manual tally was -4.8 steps (-1.8%). Intraclass correlation coefficients for step counts and 2-minute walk, standing balance, and 4-meter gait speed at discharge were 0.41 (95% CI -0.14 to 0.75), -0.12 (95% CI -0.67 to 0.64), and 0.17 (95% CI -0.46 to 0.66), respectively. Values were similarly poor at 30 days.ConclusionsThe use of consumer-grade Fitbit Charge HR in patients with recent mild stroke is feasible with reasonable adherence and accuracy. There was poor correlation between step counts and gait speed, balance, and endurance. Further research is needed to evaluate the association between step counts and other outcomes relevant to patients, including patient-reported outcomes and measures of physical function.

Project description:IntroductionWhile functional near-infrared spectroscopy (fNIRS) can provide insight into motor-cognitive deficits during ecologically valid gait conditions, the feasibility of using fNIRS during complex walking remains unknown. We tested the process and scientific feasibility of using an fNIRS device to measure cortical activity during complex walking tasks consisting of straight walking and navigated walking under single and dual-task (DT) conditions.MethodsNineteen healthy people from 18 to 64 years (mean age: 45.7 years) participated in this study which consisted of three complex walking protocols: (i) straight walking, DT walking (walking while performing an auditory Stroop task) and single-task auditory Stroop, (ii) straight and navigated walking, and (iii) navigated walking and navigated DT walking. A rest condition (standing still) was also included in each protocol. Process feasibility outcomes included evaluation of the test procedures and participant experience during and after each protocol. Scientific feasibility outcomes included signal quality measures, and the ability to measure changes in concentration of deoxygenated and oxygenated hemoglobin in the prefrontal cortex.ResultsAll participants were able to complete the three protocols with most agreeing that the equipment was comfortable (57.9%) and that the testing duration was adequate (73.7%). Most participants did not feel tired (94.7%) with some experiencing pain (42.1%) during the protocols. The signal qualities were high for each protocol. Compared to the rest condition, there was an increase in oxygenated hemoglobin in the prefrontal cortex when performing dual-task walking and navigation.ConclusionWe showed that our experimental setup was feasible for assessing activity in the prefrontal cortex with fNIRS during complex walking. The experimental setup was deemed acceptable and practicable. Signal quality was good during complex walking conditions and findings suggest that the different tasks elicit a differential brain activity, supporting scientific feasibility.

Project description:BackgroundAlzheimer's disease (AD) is the most common and most costly chronic neurodegenerative disease globally. AD develops over an extended period prior to cognitive symptoms, leaving a "window of opportunity" for targeted risk-reduction interventions. Further, this pre-dementia phase includes early physiological changes in sleep and autonomic regulation, for which wearable biosensor devices may offer a convenient and cost-effective method to assess AD-risk.MethodsPatients with a family history of AD and no or minimal cognitive complaints were recruited from the Alzheimer's Prevention Clinic at Weill Cornell Medicine and New York-Presbyterian. Of the 40 consecutive patients screened, 34 (85%) agreed to wear a wearable biosensor device (WHOOP). One subject (2.5%) lost the device prior to data collection. Of the remaining subjects, 24 were classified as normal cognition and were asymptomatic, 6 were classified as subjective cognitive decline, and 3 were amyloid-positive (one with pre-clinical AD, one with pre-clinical Lewy-Body Dementia, and one with mild cognitive impairment due to AD). Sleep-cycle, autonomic (heart rate variability [HRV]) and activity measures were collected via WHOOP. Blood biomarkers and neuropsychological testing sensitive to cognitive changes in pre-clinical AD were obtained. Participants completed surveys assessing their sleep-patterns, exercise habits, and attitudes towards WHOOP. The goal of this prospective observational study was to determine the feasibility of using a wrist-worn biosensor device in patients at-risk for AD dementia. Unsupervised machine learning was performed to first separate participants into distinct phenotypic groups using the multivariate biometric data. Additional statistical analyses were conducted to examine correlations between individual biometric measures and cognitive performance.Results27 (81.8%) participants completed the follow-up surveys. Twenty-four participants (88.9%) were satisfied with WHOOP after six months, and twenty-three (85.2%) wanted to continue wearing WHOOP. K-means clustering separated participants into two groups. Group 1 was older, had lower HRV, and spent more time in slow-wave sleep (SWS) than Group 2. Group 1 performed better on two cognitive tests assessing executive function: Flanker Inhibitory Attention/Control (FIAC) (p=.031), and Dimensional Change Card Sort (DCCS) (p=.061). In Group 1, DCCS was correlated with SWS (ρ=.68, p=0.024) and HRV (ρ=.6, p=0.019). In Group 2, DCCS was correlated with HRV (ρ=.55, p=0.018). There were no significant differences in blood biomarkers between the two groups.ConclusionsWearable biosensor devices may be a feasible tool to assess AD-related physiological changes. Longitudinal collection of sleep and HRV data may potentially be a non-invasive method for monitoring cognitive changes related to pre-clinical AD. Further study is warranted in larger populations.

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Relearning functional and symmetric walking after stroke using a wearable device: a feasibility study.

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Relearning functional and symmetric walking after stroke using a wearable device: a feasibility study.

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