Additional effect of iyengar yoga and EMG biofeedback on pain and functional disability in chronic unilateral knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: There are limited data about Iyengar Yoga and EMG biofeedback in knee OA, although the efficacy of EMG biofeedback in the rehabilitation of patients with quadriceps muscle weakness secondary to immobilization, contracture, and joint surgery has been well established. MATERIALS AND METHODS: Thirty subjects who have fulfilled inclusion and exclusion criteria were selected and divided into two groups (Group A and B). Both the groups were treated with EMG biofeedback, knee muscle strengthening exercises, and TENS. Group A received additionally Iyengar Yoga for 8 weeks. Both groups were evaluated by Visual Analog Scale and Modified WOMAC-Western Ontario McMaster Universities Scale. RESULTS: Patients in both groups experienced significant reduction in pain and improvement in functional ability. In VAS scale Group A showed reduction of 56.83% (P = 0.001) when compared with Group B 38.15% (P ≤ 0.001). In modified WOMAC Scale, Group A showed reduction of 59.21% (P = 0.001) when compared with Group B 34.08% (P = 0.001). CONCLUSION: Adding Iyengar Yoga along with conventional therapy provides better results in chronic unilateral knee osteoarthritis in terms of pain and functional disability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".