Is Perceived Exertion a Useful Indicator of the Metabolic and Cardiovascular Responses to a Metabolic Conditioning Session of Functional Fitness?
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Bibliographic record
Abstract
The purpose of this study was to assess whether the self-regulation of training intensity based on rating of perceived exertion (RPE) is a reliable method to control the intensity during metabolic conditioning sessions of functional fitness. In addition, the relationship between RPE and the changes in heart rate, number of repetitions, and lactate responses was also analyzed. Eight male participants (age 28.1 ± 5.4 years; body mass 77.2 ± 4.4 kg; VO2 max: 52.6 ± 4.6 mL·(kg·min)−1 completed two sessions (five to seven days apart), in a randomized order, under different conditions, as follows: (1) all-out (ALL), or (2) self-regulation of intensity based on an RPE of six (hard) on the Borg CR-10 scale (RPE6). The rating of perceived exertion, lactate (LAC), and heart rate (HR) response were measured before, during, and immediately after the sessions. The RPE and LAC during the all-out sessions were higher (p < 0.0005) than the RPE6 session for all of the analyzed time points during the session. There was no difference in the HR area under the curve for the all-out and RPE6 sessions. The average number of repetitions performed was lower (p ≤ 0.009) for the RPE6 session (190.5 ± 12.5 repetitions) when compared to the all-out session (214.4 ± 18.6 repetitions). There was a significant correlation between the RPE and LAC (p = 0.005; r = 0.66; large) and number of repetitions during the session (p = 0.026; r = 0.55; large). No correlation was observed between the RPE and HR (p = 0.147; r = 0.380). These results indicate that the self-regulation of intensity of effort based on the RPE may be a useful tool to control the exercise intensity during a metabolic conditioning session of functional fitness.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 it