Endurance Running Training Individually Guided by HRV in Untrained Women
Bibliographic record
Abstract
Abstract da Silva, DF, Ferraro, ZM, Adamo, KB, and Machado, FA. Endurance running training individually guided by HRV in untrained women. J Strength Cond Res 33(3): 736–746, 2019—The aim of this study was to analyze the effects of heart rate variability (HRV)-guided training compared with a standardized prescription on (a) time to complete 5-km running performance (t5km), (b) peak treadmill running speed ( V peak) and its time limit ( t lim at V peak), and (c) autonomic cardiac modulation (i.e., parasympathetic activity and recovery) in untrained women. Additionally, we correlated changes in t5km with changes in V peak, t lim at V peak and autonomic cardiac modulation. Thirty-six untrained women were divided into a HRV-guided training group (HRVG) and a control group (CG). The CG followed a predefined program, alternating moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT). The determination of MICT or HIIT was based on the pretraining HRV for HRVG. MICT was performed if HRV was SD of previous measures. Otherwise, HIIT was prescribed. The t5km, V peak, t lim at V peak, parasympathetic activity (i.e., rMSSD) and parasympathetic reactivation (i.e., HRR) were measured before and after the training period. The t5km decreased to a greater magnitude in the HRVG (−17.5 ± 5.6% vs. −14 ± 4.7%; Effect Size (ES) between-group difference = moderate). rMSSD and t lim at V peak only improved in HRVG (+23.3 ± 27.8% and +23.6 ± 31.9%, respectively). The HRVG experienced greater improvements in V peak and HRR ( V peak: 10 ± 7.3% vs. 8.2 ± 4.7%; HRR: 19.1 ± 28.1% vs. 12.6 ± 12.9%; ES between-group difference = small). Although HRVG performed less MICT than CG, the volume of MICT was negatively related to changes in t5km. V peak changes were highly correlated with t5km changes. The greater improvements in HRVG for t5km and autonomic modulation reinforce the potential application of this tool.
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 | 0.000 |
| 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".