Objective and subjective measures of exercise intensity during thermo-neutral and hot yoga
Bibliographic record
Abstract
While hot yoga has gained enormous popularity in recent years, owing in part to increased environmental challenge associated with exercise in the heat, it is not clear whether hot yoga is more vigorous than thermo-neutral yoga. Therefore, the aim of this study was to determine objective and subjective measures of exercise intensity during constant intensity yoga in a hot and thermo-neutral environment. Using a randomized, crossover design, 14 participants completed 2 identical ∼20-min yoga sessions in a hot (35.3 ± 0.8 °C; humidity: 20.5% ± 1.4%) and thermo-neutral (22.1 ± 0.2 °C; humidity: 27.8% ± 1.6%) environment. Oxygen consumption and heart rate (HR) were recorded as objective measures (percentage of maximal oxygen consumption and percentage of maximal HR (%HRmax)) and rating of perceived exertion (RPE) was recorded as a subjective measure of exercise intensity. There was no difference in exercise intensity based on percentage of maximal oxygen consumption during hot versus thermo-neutral yoga (30.9% ± 2.3% vs. 30.5% ± 1.8%, p = 0.68). However, exercise intensity was significantly higher during hot versus thermo-neutral yoga based on %HRmax (67.0% ± 2.3% vs. 60.8% ± 1.9%, p = 0.01) and RPE (12 ± 1 vs. 11 ± 1, p = 0.04). According to established exercise intensities, hot yoga was classified as light-intensity exercise based on percentage of maximal oxygen consumption but moderate-intensity exercise based on %HRmax and RPE while thermo-neutral yoga was classified as light-intensity exercise based on percentage of maximal oxygen uptake, %HRmax, and RPE. Despite the added hemodynamic stress and perception that yoga is more strenuous in a hot environment, we observed similar oxygen consumption during hot versus thermo-neutral yoga, classifying both exercise modalities as light-intensity exercise.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".