Neuromechanical Differences between Pronated and Supinated Forearm Positions during Upper-Body Wingate Tests
Bibliographic record
Abstract
Arm-cycling is a versatile exercise modality with applications in both athletic enhancement and rehabilitation, yet the influence of forearm orientation remains understudied. Thus, this study aimed to investigate the impact of forearm position on upper-body arm-cycling Wingate tests. Fourteen adult males (27.3 ± 5.8 years) underwent bilateral assessments of handgrip strength in standing and seated positions, followed by pronated and supinated forward arm-cycling Wingate tests. Electromyography (EMG) was recorded from five upper-extremity muscles, including anterior deltoid, triceps brachii lateral head, biceps brachii, latissimus dorsi, and brachioradialis. Simultaneously, bilateral normal and propulsion forces were measured at the pedal-crank interface. Rate of perceived exertion (RPE), power output, and fatigue index were recorded post-test. The results showed that a pronated forearm position provided significantly (p < 0.05) higher normal and propulsion forces and triceps brachii muscle activation patterns during arm-cycling. No significant difference in RPE was observed between forearm positions (p = 0.17). A positive correlation was found between seated handgrip strength and peak power output during the Wingate test while pronated (dominant: p = 0.01, r = 0.55; non-dominant: p = 0.03, r = 0.49) and supinated (dominant: p = 0.03, r = 0.51; don-dominant: p = 0.04, r = 0.47). Fatigue changed the force and EMG profile during the Wingate test. In conclusion, this study enhances our understanding of forearm position's impact on upper-body Wingate tests. These findings have implications for optimizing training and performance strategies in individuals using arm-cycling for athletic enhancement and rehabilitation.
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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 | 0.001 |
| 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".