The Effect of Contralateral Submaximal Contraction on the Development of Biceps Brachii Muscle Fatigue
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine if a submaximal contraction in the contralateral limb affected the fatigability of the dominant limb. BACKGROUND: Muscle fatigue is a known risk factor for musculoskeletal injury; however, it is unknown whether a submaximal contraction in the nondominant limb, such as for stabilizing a tool or load, affects the rate of development of fatigue, potentially increasing risk of injury. Current ergonomic assessments of injury risk do not involve consideration of submaximal contralateral demands. It was hypothesized that increased neuromuscular drive and active muscle mass during bilateral contractions would increase fatigability. METHOD: Twelve males isometrically maintained a 30% unilateral contraction and a 30% dominant + 15% nondominant bilateral contraction until failure on two different collection days, separated by 7 days. RESULTS: No statistically significant differences were found for time to task failure (p = .6204), decrease in maximal force (p = .1698), or alterations in electromyography amplitude (p = .7223) or frequency (p = .3292) between unilateral and bilateral conditions. CONCLUSION: The hypothesis that the addition of a lesser submaximal isometric contraction would increase fatigability was rejected. APPLICATION: These findings indicate that in ergonomic settings, muscle fatigability can be estimated by the more demanding task and do not need to be complicated by lesser submaximal contractions in the opposing limb.
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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) | 0.003 | 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".