Changes of Pedaling Technique and Muscle Coordination during an Exhaustive Exercise
Bibliographic record
Abstract
PURPOSE: Alterations of the mechanical patterns during an exhaustive pedaling exercise have been previously shown. We designed the present study to test the hypothesis that these alterations in the biomechanics of pedaling, which occur during exhaustive exercise, are linked to changes in the activity patterns of lower limb muscles. METHODS: Ten well-trained cyclists were tested during a limited time to exhaustion, performing 80% of maximal power tolerated. Pedal force components were measured continuously using instrumented pedals and were synchronized with surface EMG signals measured in 10 lower limb muscles. RESULTS: The results confirmed most of the alterations of the mechanical patterns previously described in the literature. The magnitude of the root mean squared of the EMG during the complete cycle (RMScycle) for tibialis anterior and gastrocnemius medialis decreased significantly (P < 0.05) from 85% and 75% of Tlim, respectively. A higher RMScycle was obtained for gluteus maximus (P < 0.01) and biceps femoris (P < 0.05) from 75% of Tlim. The k values that resulted from the cross-correlation technique indicated that the activities of six muscles (gastrocnemius medialis, gastrocnemius lateralis, tibialis anterior, vastus lateralis, vastus medialis, and rectus femoris) were shifted forward in the cycle at the end of the exercise. CONCLUSIONS: The large increases in activity for gluteus maximus and biceps femoris, which are in accordance with the increase in force production during the propulsive phase, could be considered as instinctive coordination strategies that compensate for potential fatigue and loss of force of the knee extensors (i.e., vastus lateralis and vastus medialis) by a higher moment of the hip extensors.
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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 | 0.000 | 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".