Sex-specific myoelectric manifestations of localized fatigue during a multi-joint repetitive task
Bibliographic record
Abstract
We have previously demonstrated that fatigue at different locations impacts joint angles, angular variability, and coordination variability differently. However, the neuromuscular control aspects underlying these kinematic changes have never been demonstrated. Seventeen young adults (8 males) were recruited. Electromyographic electrodes were placed on: upper trapezius, pectoralis major, anterior and middle deltoid, biceps and triceps brachii, and left and right erector spinae. Subjects performed the repetitive pointing task (RPT) at 1 Hz for 30 s before and after localized fatigue tasks, which consisted of one shoulder, one elbow and one lower back isometric fatiguing protocols until exhaustion in randomized order. Electromyographic amplitude (RMS), variability (SD) and mean power frequency (MnPF) were calculated for each of the pre-fatigue and post-fatigue RPT trials. There were sex × fatigue location interaction effects on upper trapezius RMS (p = 0.038) with males' values increasing the most after shoulder fatigue. Females' triceps brachii RMS was greater compared to males after shoulder, elbow, and trunk fatigue (p = 0.003, p = 0.001 and p = 0.007 respectively). There were sex × fatigue location effects on left erector spinae MnPF (p = 0.011) with males and females' values decreasing the most after trunk fatigue, but more so in males. Results demonstrate that males and females compensate differently during a repetitive pointing task when their elbows, shoulders and trunks are locally fatigued, which could have implications on sex-specific workplace injury risks. See Table 1 for acronyms.
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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) | 0.003 | 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".