Repeatability of surface EMG-based single parameter muscle fatigue assessment strategies in static and cyclic contractions
Bibliographic record
Abstract
The repeatability of a spectral surface electromyography-based fatigue assessment strategy was evaluated. Variability of two fatigue-trend tracking parameters was used as an indicator for repeatability. The parameters were the natural logarithm of the slope of linear mean frequency decline lnMF(S) and the percent drop in mean frequency MF(D). The coefficient of variation CoV was used as the metric for repeatability, representing the ratio of the standard deviation to the mean of repeated measures from the same individual. Five weekly fatigue tests on the right biceps brachii were conducted on 11 participants with a fatiguing regime comprising of alternating static and cyclic segments, collecting seven channels of differential EMG. The resulting 95% confidence intervals of the CoV were: 15.38-24.87% (Static lnMF(S)), 12.21-23.36% (Cyclic lnMF(S)), 13.18-21.85% (Static MF(D)), and 12.37-24.39% (Cyclic MF(D)). There was no statistically significant difference in repeatability between any combination of parameter and types of motion.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".