Sensitivity of 24-h EMG duration and intensity in the human vastus lateralis muscle to threshold changes
Bibliographic record
Abstract
Few studies have quantified lower limb muscle activity over 24 h using electromyographic signals (EMG). None have described the changes in EMG duration and intensity when data are analyzed with different thresholds. Continuous bilateral EMG recordings were made from vastus lateralis (VL) in 10 subjects (20-48 yr) for 24 h. Before and after this recording, voluntary quadriceps forces and VL EMG at 25%, 50%, 75%, and 100% of the maximal voluntary contraction (MVC), percentage voluntary activation (twitch interpolation), and compound action potentials (M-waves) were recorded. Offline, the 24-h EMG integrals (IEMG, 10-ms time constant) were normalized to the MVC IEMG. Total EMG duration and mean IEMG ranged from 1-3 h and 3.2-12.1% MVC, respectively, when the data were analyzed using the baseline (+3 SD) as threshold. When analysis was done with progressively higher thresholds, from baseline up to 4% MVC, the total EMG duration declined curvilinearly. In some cases the decline in duration was 50-60% for a 1% MVC threshold increment. The mean 24-h IEMG increased by 1.5-2% MVC for each 1% MVC threshold increment. Hence, a small change in the analysis threshold may result in large changes in 24-h EMG duration but moderate changes in mean IEMG. Our findings suggest that VL was active for a short amount of time and at low intensities over 24 h.
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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 | 0.001 | 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) | 0.001 | 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".