ArticleScientific reports2025
Individual training prescribed by heart rate variability, heart rate and well-being scores in experienced cyclists.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Exercise-induced neuropeptidergic and neurochemical neuroadaptation in stress regulation and emotional disorders.Acta neurologica Belgica · 2026Review
- A Narrative Review of HRV Metric Selection for Applied Monitoring: RMSSD as the Default Metric for Sport and Exercise.Journal of functional morphology and kinesiology · 2026Review
- Predicting Next Day Heart Rate Variability Based on Training Load in Cyclists Using Machine Learning.Sports (Basel, Switzerland) · 2026Article
- Artificial Intelligence in Sports Medicine: A Decision-Centered Framework for the Future Sports Physician.Diagnostics (Basel, Switzerland) · 2026Review
- Integrating the Contrasting Perspectives Between the Constrained Disorder Principle and Deterministic Optical Nanoscopy: Enhancing Information Extraction from Imaging of Complex Systems.Bioengineering (Basel, Switzerland) · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Optimizing the training of endurance athletes involves the nuanced balance between overload and recovery. Monitoring recovery effectively requires integrating multiple variables. This study evaluates the efficacy of training protocols guided by vagally-mediated heart rate variability (vmHRV), resting heart rate (RHR), and subjective well-being (WB) scores in improving cycling performance. It also explores the relationships between physiological and subjective measures. Twenty-eight experienced male cyclists were divided into three groups: vmHRV-only (Group 1), vmHRV + WB (Group 2), and vmHRV + WB + RHR (Group 3). Over 40 days, participants recorded daily vmHRV, RHR, and WB scores and followed customised training protocols. Pre- and post-intervention cycling tests assessed maximal power (Pmax), 1-min, 5-min, 20-min, and functional threshold power (FTP™). Daily data analysis included correlation and autocorrelation function (ACF) assessments to evaluate trends and individual variability. Across all groups, significant performance improvements were observed for 1-min, 5-min, 20-min, FTP™, and FTP™/kg. Group 3 showed the greatest improvements, particularly in 5-min and 20-min efforts (310.5 ± 60 to 337.9 ± 71 watts, and 260.9 ± 55 to 284.5 ± 64 watts, respectively). ACF revealed stress as having the highest day-to-day consistency among subjective measures. Individual correlations revealed diverse strengths of the relationships between physiological and subjective markers. Combining vmHRV, RHR, and WB offers a more nuanced assessment of athlete readiness and enhances training outcomes compared to vmHRV-only guidance. The study underscores the value of integrating physiological and subjective measures for personalising training protocols and highlights future directions for improving monitoring systems with advanced analytics.
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Registered trials
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