Functional Electrical Stimulation Cycling Exercise in People with Multiple Sclerosis
Bibliographic record
Abstract
Abstract Background: Functional electrical stimulation (FES) cycling is an advanced rehabilitation modality that involves systematic mild electrical stimulation of focal muscle groups to produce leg cycling movement against an adjustable work rate. The present study reports on the efficacy of an assessor-blinded, pilot randomized controlled trial of supervised FES cycling exercise in people with multiple sclerosis (MS) on secondary trial outcomes, including cognition, fatigue, pain, and health-related quality of life. Methods: Eleven adult participants with MS were randomized to receive FES cycling exercise (n = 6) or passive leg cycling (n = 5) for 24 weeks. Cognitive processing speed was assessed using the Symbol Digit Modalities Test. Symptoms of fatigue and pain were assessed using the Fatigue Severity Scale, the Modified Fatigue Impact Scale, and the short-form McGill Pain Questionnaire. Physical and psychological health-related quality of life were assessed using the 29-item Multiple Sclerosis Impact Scale. Results: Eight participants (four, FES; four, passive leg cycling) completed the intervention and outcome assessments. The FES cycling exercise resulted in moderate-to-large improvements in cognitive processing speed (d = 0.53), fatigue severity (d = −0.92), fatigue impact (d = −0.45 to −0.68), and pain symptoms (d = −0.67). The effect of the intervention on cognitive performance resulted in a clinically meaningful change, based on established criteria. Conclusions: We provide preliminary evidence for the benefits of FES cycling exercise on cognition and symptoms of fatigue and pain. Appropriately powered randomized controlled trials of FES cycling exercise are necessary to determine its efficacy for people with MS.
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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 | 0.001 |
| 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".