Shorter High-Intensity Cycling Intervals Reduce Performance and Perceived Fatigability at Work-Matched but Not Task Failure
Bibliographic record
Abstract
INTRODUCTION: The intensity, duration, and distribution of work and recovery phases during high-intensity interval training (HIIT) modulate metabolic perturbations during exercise and subsequently influence the development of performance fatigability and exercise tolerance. This study aimed to characterize neuromuscular, perceptual, and cardiorespiratory responses to work-to-rest ratio-matched HIIT protocols differing in work and rest interval duration. METHODS: Twelve healthy individuals (six women) first completed a ramp incremental test to determine 90% of peak power output, and then in three randomized visits, they completed three cycling protocols to task failure at 90% of peak power output: (i) 3- to 3-min work-to-passive rest ratio HIIT (HIIT 3min ), (ii) 1- to 1-min work-to-passive rest ratio HIIT (HIIT 1min ), and (iii) constant load (CL). Interpolated twitch technique, including maximal voluntary isometric knee extensions and femoral nerve electrical stimuli, was performed at baseline, every 6 min of work, and task failure. Perceptual and cardiorespiratory responses were recorded every 3 min and continuously across the exercises, respectively. RESULTS: The work completed during HIIT 1min (8447 ± 5124 kJ) was considerably greater than HIIT 3min (1930 ± 712 kJ) and CL (1076 ± 356) ( P < 0.001). At work-matched, HIIT 1min resulted in a lesser decline in maximal voluntary contraction and twitch force compared with HIIT 3min and CL ( P < 0.001). Perceived effort, pain, and dyspnea were least in HIIT 1min and HIIT 3min compared with CL ( P < 0.001). At task failure, HIIT 1min resulted in less voluntary activation than HIIT 3min ( P = 0.010) and CL ( P = 0.043), and engendered less twitch force decline than CL ( P = 0.021). CONCLUSIONS: Overall, the mitigated physiological and perceptual responses during shorter work periods (HIIT 1min ) enhance exercise tolerance in comparison to longer work intervals at the same intensity (HIIT 3min , CL).
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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) | 0.002 | 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".