Exploring the acute muscle fatigue response in resistance trained individuals during eccentric quasi-isometric elbow flexions—a cross-sectional comparison of repetition and sex
Bibliographic record
Abstract
Eccentric quasi-isometrics (EQIs) are a novel, low-velocity resistance exercise technique that incorporates a holding isometric contraction to positional fatigue, followed by voluntary resistance of the resulting eccentric muscle action. As females are typically more fatigue resistant than males during isometric and low-velocity dynamic muscle actions, this study explored sex-differences in the muscle fatigue response to an EQI protocol. Twenty-five (n = 12 female) participants completed 4 unilateral EQI elbow flexions. Absolute and relative surface electromyography (sEMG) amplitude (iEMG, LE peak), mean power frequency (MPF), angular impulse (aIMP), and elbow angle were compared across repetitions and between sexes using discrete values and statistical parametric/non-parametric mapping. There were significant and substantial sex and repetition differences in absolute iEMG, MPF, and aIMP, however, males and females had statistically similar absolute aIMP by repetition 4. When expressed relatively, there were no significant sex-differences. Additionally, there were significant between repetition changes in sEMG amplitude and elbow angle with an increasing number of repetitions, largely in the first-two thirds of repetition time. The current study suggests that there are absolute, but not relative sex-differences in EQI induced muscle fatigue, and the effects across repetitions occur predominately in the first two-thirds of repetition time.
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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) | 0.002 | 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".