Single‐vs. double‐leg cycling: lower cardiorespiratory demands and perceived effort for a greater relative power output
Bibliographic record
Abstract
Single‐leg cycling is an insightful model of unilateral exercise. It affords a unique comparison of exercise interventions in a within‐subject manner, as the addition of a counterweight to the contralateral pedal facilitates the ‘feel’ of normal double‐leg cycling. The present study characterized physiological responses to single‐ and double‐leg cycling performed at the same relative intensities in twelve men (age: 21 ± 2 years; BMI: 24 ± 3 kg/m 2 ). Graded‐exercise tests initially established that peak oxygen uptake (VO 2 peak ; +31%), ventilation (V E peak ; +33%), heart rate (HR peak ; +9%), and power output (PPO; +78%) were higher (main effect of mode; p < 0.05) during double‐compared to single‐leg cycling. On separate days, subjects subsequently performed four experimental trials, which involved 30‐min bouts of either moderate‐intensity continuous training (MICT) or high‐intensity interval training (HIIT) in a single‐ or double‐leg manner. Although performed at the same percentage of the respective PPO, single‐leg exercise elicited a greater average power output per leg than double‐leg exercise (+13%; p < 0.001). In contrast, average EMG responses from the vastus lateralis and vastus medialis were similar for single‐ and double‐leg cycling (p > 0.05), although the semitendinosus was activated to a greater extent for single‐leg cycling relative to double‐leg cycling (p < 0.001). Single‐leg cycling elicited markedly lower V E , VO 2 , and HR responses and ratings of perceived exertion compared to double‐leg cycling (p < 0.05). In summary, single‐leg cycling allows for a greater power output (per leg) than double‐leg cycling, while eliciting lower cardiorespiratory and perceptual responses. Support or Funding Information Natural Sciences and Engineering Research Council of Canada (NSERC)
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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".