Response In Heart Rate Variability To On-ice Exercise Stress In Female Collegiate Ice Hockey Players
Bibliographic record
Abstract
Female collegiate hockey players experience elevated and sustained cardiovascular function during training and competition. Understanding the dose-response to exercise is critical for coaches and practitioners for adjusting training sessions to allow for recovery. PURPOSE: To examine alterations in heart rate variability (HRV) in response to heart rate (HR) derived training loads in female collegiate hockey players. METHODS: Twenty-one healthy female collegiate hockey players with an age of (mean ± SD) 20.4 ± 1.7 y, a height of 166.3 ± 4.7 cm, and a body weight of 66.4 ± 7.3 kg volunteered for a 20-day study period. Daily exercise stress was recorded during on ice training sessions and competition using a chest strap heart rate monitor. Data was collected from the beginning of dryland warmup and concluded after the off-ice cool down. Exercise stress was quantified using heart rate dynamics and calculated using Edwards training load. Daily HRV was analyzed immediately upon awakening each morning in the supine position. A chest strap heart rate monitor was utilized to record R-R intervals over a 30s recording period and were exported into a smartphone application for HRV analysis. The root mean squared of successive differences between cardiac cycles (rMSSD) was calculated. Linear regression was utilized to examine the association between HRV and HR derived training loads. Significance was declared as p < 0.05. The study was approved by the Research Ethics Review Board of the University of Windsor. RESULTS: Weekly training load (mean ± SD) was 212.3 ± 190.2 (AU). Weekly rMSSD (mean ± SD) was 91.5 ± 14.8 (ms). A significant association between daily rMSSD and HR-derived training loads were observed as displayed through a coefficient of determination of (R2 = 0.47. p < 0.001) and a Pearson correlation coefficient of (r 95% CI = 0.69, 0.36: 0.87) CONCLUSION: The results from this study demonstrate daily rMSSD is significantly associated with HR derived training loads. HRV may be a viable option to monitor the physiological response from on-ice training and competition in female collegiate hockey players.
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 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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".