Localized muscle vibration reverses quadriceps muscle hypotrophy and improves physical function: a clinical and electrophysiological study
Bibliographic record
Abstract
Quadriceps weakness has been associated with knee osteoarthritis (OA). High-frequency localized muscle vibration (LMV) has been proposed recently for quadriceps strengthening in patients with knee OA. The purpose of this study was (a) to investigate the clinical effectiveness of high-frequency LMV on quadriceps muscle in patients with knee OA and (b) to disentangle, by means of surface electromyography (sEMG), the underlying mechanism. Thirty patients, aged between 40 and 65 years, and clinically diagnosed with knee OA were included in this randomized, controlled, single-blinded pilot study. Participants were randomly assigned to two groups: a study group treated with LMV, specifically set for muscle strengthening (150 Hz), by means of a commercial device VIBRA, and a control group treated with neuromuscular electrical stimulation. Clinical outcome was measured using the Western Ontario and McMaster Universities Osteoarthritis Index, Visual Analogue Scale, knee range of motion, Timed Up and Go test, and Stair climbing test. To assess changes in muscle activation and fatigue a subgroup of 20 patients was studied with the use of sEMG during a sustained isometric contraction. The LMV group showed a significant change in Western Ontario and McMaster Universities Osteoarthritis Index score, Visual Analogue Scale score, Timed Up and Go test, Stair Climbing Test, and knee flexion. These improvements were not significant in patients treated with neuromuscular electrical stimulation. sEMG analysis suggested an increased involvement of type II muscle fibers in the group treated with LMV. In conclusion, the present study supports the effectiveness of local vibration in muscle function and clinical improvement of patients with knee OA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".