Fatigue and Recovery of Power and Torque During Isotonic Knee Extensions in Young Men
Bibliographic record
Abstract
1894 The effect of velocity on power and torque during neuromuscular fatigue and recovery has not been evaluated in humans. PURPOSE: To compare the fatigue and recovery of maximum isometric torque (MVC) and peak velocity (Vpeak) during power loss induced by isotonic contractions in young men. METHODS: Using a Biodex System 3 dynamometer, seven men (26 ± 2 y, 174 ± 6 cm, 73 ± 7 kg) performed fatiguing isotonic (40% MVC every 1.5s through 75 deg range of motion) single-limb knee extensions at Vpeak, until Vpeak was reduced by 35%. Recovery of Vpeak and MVC were measured at 0.5, 1.5, 3, 5, and 10 minutes. RESULTS: During the fatiguing protocol, both Vpeak and average power were unchanged for 25% of the endurance time, but declined linearly during the remainder of the protocol. Endurance times ranged from 42 to 72 seconds. By the end of the fatiguing task, baseline MVC (262 ± 31 Nm) and Vpeak (350 ± 31 deg/s) declined to 74 ± 7% (193 ± 27 Nm) and 62 ± 3% (218 ± 19 deg/s), respectively. Also, average power decreased to 60 ± 5% (186 ± 20 W) of baseline (310 ± 37 W). By 0.5 minutes of recovery, Vpeak was 91 ± 8% of baseline and fully recovered at 3 minutes, whereas MVC was depressed at 0.5 minutes recovery (71 ± 3% of baseline MVC) and recovered only to 81 ± 7% of baseline MVC at 10 minutes. Average power recovered to 82 ± 9% of baseline at 0.5 minutes and was recovered fully at 5 minutes. CONCLUSION: At a moderate workload, the fatigue and recovery of power appears more closely related to changes in Vpeak than MVC. Furthermore, the isolated assessment of MVC or velocity does not fully explain fatigue and recovery of power during isotonic contractions. Supported by NSERC and CIHR.
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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".