Moving towards precision post-stroke rehabilitation: A systematic review and meta-analysis of wearable sensor-derived walking activities in daily living
Bibliographic record
Abstract
Abstract Background Physical rehabilitation interventions can enhance functional capacity after stroke, but improved ability doesn’t always lead to better real-world performance. Understanding this gap is key to optimizing post-stroke recovery strategies. Objectives This research aimed to evaluate the effectiveness of physical rehabilitation interventions specifically exercise, behavior change techniques (BCTs), or their combination on real-world walking measured using wearable sensors and capacity (gait speed and walking endurance) outcomes in stroke survivors. Methods This systematic review and meta-analysis followed PRISMA guidelines. Comprehensive searches were conducted in Medline, Embase, CINAHL, and Scopus up to January 2025. Randomized controlled trials involving stroke survivors receiving physical rehabilitation interventions—exercise, BCTs, or both—compared to exercise-only or usual care were included. Outcomes assessed were daily steps, gait speed (comfortable and fastest), and endurance (6-minute walk test). Meta-analyses using random-effects models (STATA 18) reported standardized mean differences (SMDs) and 95% confidence intervals (CIs). Heterogeneity was evaluated using I² statistics. Results Of 1,782 references screened, 28 studies met the inclusion criteria, and 23 were included in meta-analyses comprising 2,327 participants. Exercise-only interventions produced a small but significant improvement in daily steps (SMD = 0.23; 95% CI: 0.03 to 0.44; I 2 = 36.6%; moderate certainty ), and moderate improvements in both comfortable gait speed (SMD = 0.38; 95% CI: 0.19 to 0.57; I 2 = 35.5%; moderate certainty ) and endurance (SMD = 0.39; 95% CI: 0.26 to 0.52; I 2 = 0%; moderate certainty ). BCT-only interventions demonstrated a larger effect on daily steps (SMD = 0.41; 95% CI: 0.19 to 0.63; I 2 = 0%; moderate certainty). In contrast, combined exercise and BCT interventions did not yield significant improvements in any outcomes and were supported by very low to low certainty of evidence. Conclusion Exercise-only interventions improve gait speed and endurance after stroke, with small gains in daily steps. BCT-only interventions yield greater improvements in daily walking activity. Combined interventions show limited added benefit. Protocol registration This study has been registered in PROSPERO (No. CRD42023411679)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.076 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.038 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".