Wearable Technology to Capture Arm Use of People With Stroke in Home and Community Settings: Feasibility and Early Insights on Motor Performance
Bibliographic record
Abstract
OBJECTIVE: The objectives of this study were to establish the short-term feasibility and usability of wrist-worn wearable sensors for capturing the arm and hand activity of people with stroke and to explore the association between factors related to the use of the paretic arm and hand. METHODS: Thirty people with chronic stroke were monitored with wrist-worn wearable sensors for 12 hours per day for a 7-day period. Participants also completed standardized assessments to capture stroke severity, arm motor impairments, self-perceived arm use, and self-efficacy. The usability of the wearable sensors was assessed using the adapted System Usability Scale and an exit interview. Associations between motor performance and capacity (arm and hand impairments and activity limitations) were assessed using Spearman correlations. RESULTS: Minimal technical issues or lack of adherence to the wearing schedule occurred, with 87.6% of days procuring valid data from both sensors. The average sensor wear time was 12.6 (standard deviation [SD] = 0.2) hours per day. Three participants experienced discomfort with 1 of the wristbands, and 3 other participants had unrelated adverse events. There were positive self-reported usability scores (mean = 85.4/100) and high user satisfaction. Significant correlations were observed for measures of motor capacity and self-efficacy with paretic arm use in the home and the community (Spearman correlation coefficients = 0.44-0.71). CONCLUSIONS: This work demonstrates the feasibility and usability of a consumer-grade wearable sensor for capturing paretic arm activity outside the laboratory. It provides early insight into the everyday arm use of people with stroke and related factors, such as motor capacity and self-efficacy. IMPACT: The integration of wearable technologies into clinical practice offers new possibilities to complement in-person clinical assessments and to better understand how each person is moving outside of therapy and throughout the recovery and reintegration phase. Insight gained from monitoring the arm and hand use of people with stroke in the home and community is the first step toward informing future research with an emphasis on causal mechanisms with clinical relevance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".