Heart Rate Variability in Elite Swimmers before, during and after COVID-19 Lockdown: A Brief Report on Time Domain Analysis
Bibliographic record
Abstract
Background: Many athletes worldwide have endured home confinement during the COVID-19 pandemic, and their opportunities to train were strongly limited. This study describes the impact of lockdown on training volume and heart rate variability (HRV) in elite swimmers. Methods: HRV data of seven elite males were collected each Monday morning over 20 weeks, including 8 weeks of lockdown. The training volume was quantified retrospectively. Results: During the lockdown period (weeks 4–11) swimming was not allowed, and the total training volume was reduced by 55.2 ± 7.5% compared to the baseline volume (from 27.2 to 12.2 training hours). This drop was associated with a decrease in vagal activity (a 9.2 ± 5.4% increase in resting HR and a 6.5 ± 3.4% decrease in the natural logarithm of rMSSD from baseline values). After the lockdown (weeks 12–20), the training volume was gradually increased before attaining 68.8% and 88.2% of the baseline training volume at weeks 15 and 17, respectively. Resting HR and Ln rMSSD returned to baseline values four weeks after the lockdown. Conclusions: The lockdown period induced a decreased training volume which was associated with a decrease in vagal activity. However, HRV values returned to the baseline 4 weeks after the resumption of swimming training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.001 | 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".