Effect of velocity on shoulder muscle recruitment patterns during wheelchair propulsion in nondisabled individuals: Pilot study
Bibliographic record
Abstract
This study investigated how the recruitment patterns of shoulder muscles were influenced by wheelchair propulsion speed. Electromyography (EMG) activity of seven muscles was recorded with surface electrodes on 15 nondisabled subjects during wheelchair propulsion on a stationary ergometer. Kinetic data were measured by a SmartWheel. EMG total intensities were calculated to describe the muscle activation level, while the angles formed by first principal component and second principal component loading scores were calculated to describe the spectral content of EMG signals. Significant differences were observed in kinetic variables between the two testing speeds (p < 0.05). The EMG intensity of the tested muscles increased significantly with increased speed (p < 0.05). The push muscles showed a longer EMG duration, whereas the recovery muscles exhibited significantly earlier EMG onset and peak activities at the fast speed. The smaller angle values in the fast propulsion speed indicated that faster motor units were recruited to match the mechanical requirement for the faster motion. Pushing a manual wheelchair at a faster speed not only requires a higher level of propulsive muscle activity but also a higher level of recovery muscle activation.
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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 | 0.000 | 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) | 0.001 | 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".