Comparing and characterizing scapular muscle activation ratios in males and females during execution of common functional movements
Bibliographic record
Abstract
Background The shoulder complex relies on scapular movement controlled by periscapular muscles for optimal arm function. However, minimal research has explored scapular muscle activation ratios during functional tasks, nor how they might be influenced by biological sex. This investigation aims to characterize how sex impacts scapular muscle activation ratios during functional tasks. Methods Twenty participants (ten females, ten males) were assessed with surface electromyography (EMG) and motion tracking during seven functional tasks. Activation ratios were calculated from normalized EMG for the three trapezius muscles and serratus anterior. Scapular angles were calculated using a YXZ Euler sequence. Two-way mixed methods ANOVAs ( p < .05) were used to assess the effects of sex and humeral elevation level on ratios and angles. Results Sex-based differences were present in the Tie Apron task, with males exhibiting higher upper trapezius/lower trapezius and upper trapezius/middle trapezius ratios than females. Males also demonstrated decreased internal rotation in this task. Other tasks showcased significant sex-based differences in scapular upward rotation but not in activation ratios. Humeral elevation generally demonstrated an inverse relationship with scapular muscle activation ratios. Conclusions This study highlights sex-based differences in scapular muscle activation ratios during specific functional tasks, emphasizing the need to consider sex in analyses of shoulder movements. Normative activation ratios for functional tasks were provided, offering a foundation for future comparisons with non-normative groups. Further research is warranted to confirm and explore additional influencing factors, advancing our understanding of shoulder activation and movement in diverse populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".