Validity of detrended fluctuation analysis of heart rate variability to determine intensity thresholds in elite cyclists

Background: The evaluation of performance in endurance athletes and the subsequent individualisation of training is based on the determination of individual physiological thresholds during incremental tests. Gas exchange or blood lactate analysis are usually implemented for this purpose, but these m...

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Autores:
Mateo March, Manuel
MOYA-RAMÓN, MANUEL
Javaloyes, Alejandro
Sánchez Muñoz, Cristóbal
Clemente-Suárez, Vicente Javier
Tipo de recurso:
Article of journal
Fecha de publicación:
2022
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/9167
Acceso en línea:
https://hdl.handle.net/11323/9167
https://doi.org/10.1080/17461391.2022.2047228
https://repositorio.cuc.edu.co/
Palabra clave:
Thresholds
Heart rate variability
Elite cyclists
Nonlinear analysis
Rights
embargoedAccess
License
© 2022 European College of Sport Science
Description
Summary:Background: The evaluation of performance in endurance athletes and the subsequent individualisation of training is based on the determination of individual physiological thresholds during incremental tests. Gas exchange or blood lactate analysis are usually implemented for this purpose, but these methodologies are expensive and invasive. The short-term scaling exponent alpha 1 of detrended Fluctuation Analysis (DFA-α1) of the Heart Rate Variability (HRV) has been proposed as a non-invasive methodology to detect intensity thresholds. Purpose: The aim of this study is to analyse the validity of DFA-α1 HRV analysis to determine the individual training thresholds in elite cyclists and to compare them against the lactate thresholds. Methodology: 38 male elite cyclists performed a graded exercise test to determine their individual thresholds. HRV and blood lactate were monitored during the test. The first (LT1 and DFA-α1-0.75, for lactate and HRV, respectively) and second (LT2 and DFA-α1-0.5, for lactate and HRV, respectively) training intensity thresholds were calculated. Then, these points were matched to their respective power output (PO) and heart rate (HR). Results: There were no significant differences (p > 0.05) between the DFA-α1-0.75 and LT1 with significant positive correlations in PO (r = 0.85) and HR (r = 0.66). The DFA-α1-0.5 was different against LT2 in PO (p = 0.04) and HR (p = 0.02), but it showed significant positive correlation in PO (r = 0.93) and HR (r = 0.71). Conclusions: The DFA1-a-0.75 can be used to estimate LT1 non-invasively in elite cyclists. Further research should explore the validity of DFA-α1-0.5.