Effect of Functional Electrical Stimulation in Conjunction with Motor Relearning Program on Activities of Daily Living Following Ischemic Stroke: A Randomized Controlled Trial
Bibliographic record
Abstract
Background: Ischemic stroke frequently results in upper limb impairment, significantly affecting patients' ability to perform activities of daily living (ADL). Functional electrical stimulation (FES) combined with motor relearning programs has emerged as a promising rehabilitation approach for improving functional outcomes in stroke survivors. Objective: The present study evaluates the effectiveness of FES combined with motor relearning programs on ADL performance in patients with upper limb impairment following ischemic stroke. Methods: A randomised controlled trial was conducted with 84 ischemic stroke patients (mean age 58.4±12.3 years) with upper limb hemiplegia. Participants were randomly allocated to either the experimental group (n=42) receiving FES combined with motor relearning program, or the control group (n=42) receiving conventional physiotherapy. The intervention period was 6 weeks, with 5 sessions per week. The primary outcome measure was the Barthel Index (BI), and secondary outcomes included the Functional Independence Measure (FIM) and Canadian Occupational Performance Measure (COPM). Assessments were conducted at baseline, post-intervention (6 weeks), and follow-up (12 weeks). Results: Both groups showed significant improvements in ADL scores, but the experimental group demonstrated superior outcomes. At 6 weeks, the experimental group showed greater improvement in BI scores (mean difference: 15.8±8.4 vs. 8.2±6.1, p<0.001), FIM scores (mean difference: 22.3±10.7 vs. 12.1±7.9, p<0.001), and COPM performance scores (mean difference: 3.4±1.2 vs. 1.8±0.9, p<0.001). These improvements were maintained at 12-week follow-up. Conclusion: FES combined with motor relearning programs significantly enhances ADL performance in ischemic stroke patients compared to conventional therapy alone. This combined approach offers a potentially effective rehabilitation approach for improving functional independence in stroke survivors.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".