EMG-Torque Relationship and Reliability of the Medial and Lateral Hamstring Muscles
Bibliographic record
Abstract
PURPOSE: The objectives of the present investigation were to examine the EMG-joint torque relation and day-to-day reliability of the medial (MH) and lateral hamstring (LH) muscles during isometric contractions. METHODS: Twenty young adults performed five maximal voluntary isometric hamstring contractions (MVC) followed by contractions at 10%-90% MVC, in a random order. Full-wave-rectified and -integrated EMG during the middle 3 s of each contraction was expressed as a percent of the EMG during the three highest averaged MVC. A three-factor ANOVA (muscle x intensity x gender) with repeated measures was performed on normalized EMG activity. Reliability coefficients were determined for 10 randomly selected subjects that repeated the testing procedures 1 wk after the first session. RESULTS: The MH and LH EMG were observed to be significantly greater than equivalent percent MVC values at all intensity levels. A significant linear increase in MH and LH EMG was observed across contraction intensity levels, with no muscle or gender differences. Reliability was high for MH EMG across contraction intensities of 10%-60% MVC (intraclass correlation (ICC) = 0.70-0.82), moderate for the LH across 10%-30% MVC (ICC = 0.57-0.68) and the MH at 70% MVC (ICC = 0.52), and unreliable across all other contraction intensities for both muscles. CONCLUSIONS: The linear increase in MH and LH EMG, as a function of contraction intensity, was similar between both muscles but was highly reliable only for the MH during low to moderate intensities.
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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 | 0.006 |
| 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 | 0.001 |
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".