Surface Electromyographic Study of Peroneus Longus Activation during Ankle Eversion and Heel Lift
Bibliographic record
Abstract
Prophylactic and rehabilitative ankle training programs rarely incorporate ankle eversion exercises of the weight bearing leg during one-legged stand. Such training may be necessary for the optimal PL function and dynamic ankle control. In this study, we compared a PL exercise that involved eversion of the inverted ankle of a weight bearing leg against the heel lift (HL), a popular PL strengthening exercise. The PL activation patterns were studied in 20 university students (7 male and 13 female). The self-reported dominant legs of the subjects were tested in this study. After recording the surface electromyographic (EMG) activity level of their PL maximal voluntary isometric contractions (MVIC), the subjects performed HL, and ankle eversions of the weight bearing ankle during one-legged stand. Ankle eversions were initiated from two inverted ankle positions, 20 degree inversion (EV1) and 25 degree inversion (EV2). The ankle position and the PL muscle activity were recorded with an accelerometer affixed to the dorsum of the foot and a surface EMG electrode over PL respectively. The ranges of motion for HL, EV1, and EV2 were 25, 29, and 31 degrees respectively. Expressed as percentage of MVIC, the average normalized EMG linear envelopes for EV1 (73%) and EV2 (74%) were significantly greater than HL (64%). These results demonstrated that eversions of the inverted ankle of the weight bearing leg elicited stronger PL activation that may result in better lateral ankle strength and dynamic control. Incorporation of weight bearing ankle eversions may enhance effectiveness of PL exercise and balance.
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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 | 0.001 |
| 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) | 0.001 | 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".