Ankle muscle strength influence on muscle activation during dynamic and static ankle training modalities
Bibliographic record
Abstract
Muscle weakness is considered a risk factor for ankle injury. Balance training and barefoot running have been used in an attempt to strengthen the muscles crossing the ankle. It is expected that training tasks that successfully strengthen the ankle would elicit increased muscular activity. However, it is unknown how an individual's ankle strength will influence the muscle activity used during a given task. Twenty-six participants performed dynamic (shod, barefoot running) and static tasks (squat on ground, squat on ®Bosu Ball) believed to strengthen the muscles surrounding the ankle. Electromyographic signals of the tibialis anterior, peroneus longus, gastrocnemius lateralis (GL) and gastrocnemius medialis (GM) were recorded and analysed using a non-linearly scaled wavelet analysis. Participants were divided into a strong group and a weak group according to their isometric plantar-flexion torque. The weak group required more relative GL and GM muscle activity during each training task compared to the strong group. No difference was observed between shod and barefoot running. There was a significant effect of training task on muscle activation level for the weak group. Differences in ankle strength had a significant impact on muscle activation.
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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 | 0.002 |
| 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) | 0.002 | 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".