Effects of exercise on heart rate variability by time-domain, frequency-domain and non-linear analyses in equine athletes
Bibliographic record
Abstract
Background: Heart rate variability (HRV) is an intrinsic property that reflects autonomic balance and has been shown to be predictive of all-cause and cardiovascular mortality. It can be altered by physiological states such as exercise or pathological conditions. However, there are only a handful of studies on HRV in horses. The aim of this study is to compare HRV parameters before and during exercise in horses. Methods: Time-domain, frequency-domain and non-linear analyses were applied to quantify time series data on RR intervals before and during exercise in horses (n=7). Results: Exercise increased heart rate from 44±8 to 113±17 bpm (ANOVA, P <0.05) and decreased standard deviation (SD) from 7±2 to 4±2 bpm, coefficient of variation (CoV) from 16±4% to 3±2% and root mean square of successive RR interval differences (RMSSD) from 89.4±91.5 to 6.5±3.7 ms. Contrastingly, no difference in low-frequency (0.10±0.03 vs. 0.09±0.03 Hz) and high-frequency (0.19±0.03 vs. 0.18±0.03 Hz) peaks, nor in their percentage powers (2±1 vs. 4±5%; 59±9 vs. 64±20%; 39±10 vs. 32±19%) were observed but very low-frequency, low-frequency, and high-frequency powers (ms 2 ) were reduced from 29±17 to 2±5, 1138±372 to 22±22 and 860±564 to 9±6, respectively, as was total power (in logarithms) (7.52±0.52 to 3.25±0.73). Poincaré plots of RR n+1 against RR n revealed similar ellipsoid shapes before and after exercise. The SD along the line-of-identity (SD2) and SD perpendicular to the line-of-identity (SD1) were decreased by exercise (62±17 vs. 9±5 and 63±65 vs. 5±3), corresponding to increased SD2/SD1 ratio from 1.33±0.45 to 2.19±0.72. No change in approximate and sample entropy was detected (0.97±0.23 vs. 0.82±0.22 and 1.14±0.43 vs. 1.37±0.49). Detrended fluctuation analysis revealed unaltered short-term fluctuation slopes (0.76±0.27 vs. 1.18±0.55) but increased long-term fluctuation slopes (0.16±0.11 vs. 0.50±0.16) after exercise. Conclusion: Exercise leads to a decrease in HRV but did not affect signal entropy in horses.
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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 | 0.002 |
| 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) | 0.001 | 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 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".