Comparing the Effects of Rest and Massage on Return to Homeostasis Following Submaximal Aerobic Exercise: a Case Study
Bibliographic record
Abstract
INTRODUCTION: Postexercise massage can be used to help promote recovery from exercise on the cellular level, as well as systemically by increasing parasympathetic activity. No studies to date have been done to assess the effects of massage on postexercise metabolic changes, including excess postexercise oxygen consumption (EPOC). The purpose of this study was to compare the effects of massage recovery and resting recovery on a subject's heart rate variability and selected metabolic effects following a submaximal treadmill exercise session. METHODS: One healthy 24-year-old female subject performed 30 minutes of submaximal treadmill exercise prior to resting or massage recovery sessions. Metabolic data were collected throughout the exercise sessions and at three 10 minute intervals postexercise. Heart rate variability was evaluated for 10 minutes after each of two 30-minute recovery sessions, either resting or massage. RESULTS: Heart rate returned to below resting levels (73 bpm) with 30 and 60 minutes of massage recovery (72 bpm and 63 bpm, respectively) compared to 30 and 60 minutes of resting recovery (77 bpm and 74 bpm, respectively). Heart rate variability data showed a more immediate shift to the parasympathetic state following 30 minutes of massage (1.152 LF/HF ratio) versus the 30-minute resting recovery (6.91 LF/HF ratio). It took 60 minutes of resting recovery to reach similar heart rate variability levels (1.216 LF/HF) found after 30 minutes of massage. Ventilations after 30 minutes of massage recovery averaged 7.1 bpm compared to 17.9 bpm after 30 minutes of resting recovery. CONCLUSIONS: No differences in EPOC were observed through either the resting or massage recovery based on the metabolic data collected. Massage was used to help the subject shift into parasympathetic activity more quickly than rest alone following a submaximal exercise session.
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How this classification was reachedexpand
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".