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Open Access Biostatistics & Bioinformatics

Maximum Oxygen Uptake Prediction Model Based on Heart Rate Variability Parameters for Young Healthy Adult Males at Rest

  • Open or Close Wollner Materko1,2*, Rhenan Bartels1, Tiago Peçanha3, Jorge Roberto Perrout de Lima4, Alysson Roncally Silva Carvalho1,5 and Jurandir Nadal1

    1 Biomedical Engineering Program (PEB), Federal University of Rio de Janeiro, Brazil

    2 Laboratory of Human Movement Biodynamic, Federal University of Amapá, Brazil

    3 Exercise Hemodynamic Laboratory, Universidade de São Paulo, Brazil

    4 Laboratory of Motor Assessment, Universidade Federal de Juiz de Fora, Brazil

    5 Laboratory of Respiration Physiology, Universidade Federal do Rio de Janeiro, Brazil

    *Corresponding author: Wollner Materko, Section, Biomedical Engineering Program (PEB), COPPE Institute, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil and Laboratory of Human Movement Biodynamic, Physical Education, Federal University of Amapá, Brazil

Submission: August 10, 2018; Published: September 25, 2018

DOI: 10.31031/OABB.2018.02.000536

ISSN 2578-0247
Volume2 Issue3


The assessment of aerobic fitness through the measurement of maximum oxygen consumption (VO2 max) is an objective parameter that integrates cardiovascular, respiratory and metabolic responses, providing a reliable assessment of exercise capacity and health status, as well as being useful information for exercise training prescription. The purpose of this study was to determine a model for predicting Maximum Oxygen Uptake based on HRV parameters estimated at rest in 70 young physically active adults. After recording the resting tacho gram with a cardio-frequency meter to calculate HRV parameters, a maximal cardiopulmonary incremental test was performed to measure the VO2 max. The model for predicting VO2 max was obtained by stepwise multiple linear regression assuming as independent variables the mean RR interval, pNN50 index, and a proposed cardiac deceleration rate. The models were cross-validated by K-fold method, and the best model accounted for 76% of data variance, with a standard error of estimate 4.40mL·kg-1min-1. In conclusion, the obtained model might be tested as a tool for predicting the aerobic fitness in adult males in rest based on the mean RR interval and the pNN50HRV parameters. Thus, the findings are not only interesting but important in that they can be performed without the need of applying a stress test and extend the HRV applicability in the evaluation of aerobic capacity and athletic performance.

Keywords: Aerobic fitness; Cardiac deceleration rate; Heart rate variability

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