High Density EMG Spatial Distribution of the Vastus Lateralis during Isometric Knee Extension in Young and Older Men and Women
Bibliographic record
Abstract
Multichannel surface electromyography (EMG) or high density EMG (HDsEMG) can be used to study spatial distribution and muscle characteristics in aging muscle. The purpose of this study was to compare spatial EMG potential distribution during isometric knee extension between young and older men and women. Torque and HDsEMG data were recorded from the vastus lateralis during maximal voluntary isometric knee extension (MVC) from 24 young men and women (ages 19 – 25 years) and 25 older men and women (ages 64-78 years). Spatial distribution was estimated using the RMS value for each of the 32 electrode grid locations and 2-Dimensional (2D) maps were developed for each participant. Peak torque, mean EMG RMS, intensity, were compared across age and gender. Analysis of variance indicated statistically significant differences in peak torque, mean RMS and intensity between age and gender groups. Strength, muscle activation and intensity differ due to age and sex during maximal isometric knee extension. Further research that includes a larger range of submaximal and maximal contractions may provide further insight into the impact of age-related changes in muscle morphology on spatial distribution during force development.
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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 | 0.001 | 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".