The efficacy of electromyographic biofeedback on pain, function, and maximal thickness of vastus medialis oblique muscle in patients with knee osteoarthritis: a randomized clinical trial
Bibliographic record
Abstract
INTRODUCTION: The aim of this survey was to examine the effect of adding electromyographic biofeedback (EMGBF) to isometric exercise, on pain, function, thickness, and maximal electrical activity in isometric contraction of the vastus medialis oblique (VMO) muscle in patients with knee osteoarthritis (OA). METHODS: In this clinical trial, 46 patients with a diagnosis of knee OA were recruited and assigned to two groups. The case group consisted of 23 patients with EMGBF-associated exercise, and the control group was made up of 23 patients with only isometric exercise. Data were gathered via visual analog scale (VAS) score, the Persian version of the Western Ontario and McMaster Universities Osteoarthritis Index and Lequesne questionnaires, ultrasonography of the VMO, and surface electromyography of this muscle at baseline and at the end of the study. Variables were compared before and after the exercise program in each group and between the two groups. RESULTS: At the end of the study, there were no significant differences between the two groups regarding measured variables. Only the VAS score was significantly less in the case group. Although all assessed parameters, except for VMO muscle thickness, were found to be improved significantly in each group, the degree of change was not significantly different between the two groups, except for VAS score. VMO muscle thickness did not change significantly after exercise therapy in either of the groups. CONCLUSION: Isometric exercises accompanied by EMGBF and the same exercises without biofeedback for 2 months both led to significant improvements in pain and function of patients with knee OA. Real EMGBF was not superior to exercise without biofeedback in any of the measured variables, except for VAS score.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".