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A dynamical systems approach for the submaximal prediction of maximum heart rate and maximal oxygen uptake

A dynamical systems approach for the submaximal prediction of maximum heart rate and maximal... This study examines the viability of utilizing a dynamical system model and heuristic parameter estimation algorithm to make predictions for maximum heart rate ( $$\mathrm {HR_{max}}$$ HR max ) and maximal oxygen uptake ( $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max ) using data collected from a submaximal testing protocol. $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max is widely considered to be the best single measurement of overall fitness in humans. When a $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max assessment is not available, $$\mathrm {HR_{max}}$$ HR max is often used to prescribe exercise intensities for training and rehabilitation. In the absence of maximal cardiopulmonary exercise testing (CPET), $$\mathrm {HR_{max}}$$ HR max and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max are typically estimated using traditional submaximal prediction methods with well-known limitations and inaccuracies. For this study, 12 regularly exercising healthy young adult males performed a bout of maximal CPET on a cycle ergometer to determine their true $$\mathrm {HR_{max}}$$ HR max and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max . Participants also performed a submaximal bout of exercise at varied intensities. A dynamical system model and heuristic parameter estimation algorithm were applied to the submaximal data to estimate the participants’ $$\mathrm {HR_{max}}$$ HR max and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max . The submaximal predictions were evaluated by computing the coefficient of determination $${R^2}$$ R 2 and the standard error of the estimate (SEE) through comparisons with the true maximal values for $$\mathrm {HR_{max}}$$ HR max ( $${R^2 = 0.96}$$ R 2 = 0.96 , SEE = 2.4 bpm) and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max ( $${R^2 = 0.93}$$ R 2 = 0.93 , SEE = 2.1 mL kg $$^{-1}$$ - 1  min $$^{-1}$$ - 1 ). The results from this study suggest that a dynamical system model and heuristic parameter estimation algorithm can provide accurate predictions for $$\mathrm {HR_{max}}$$ HR max and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max using data collected from a submaximal testing protocol. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Sports Engineering Springer Journals

A dynamical systems approach for the submaximal prediction of maximum heart rate and maximal oxygen uptake

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References (39)

Publisher
Springer Journals
Copyright
Copyright © 2017 by International Sports Engineering Association
Subject
Engineering; Theoretical and Applied Mechanics; Engineering Design; Materials Science, general; Sports Medicine; Biomedical Engineering; Rehabilitation Medicine
ISSN
1369-7072
eISSN
1460-2687
DOI
10.1007/s12283-017-0242-1
Publisher site
See Article on Publisher Site

Abstract

This study examines the viability of utilizing a dynamical system model and heuristic parameter estimation algorithm to make predictions for maximum heart rate ( $$\mathrm {HR_{max}}$$ HR max ) and maximal oxygen uptake ( $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max ) using data collected from a submaximal testing protocol. $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max is widely considered to be the best single measurement of overall fitness in humans. When a $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max assessment is not available, $$\mathrm {HR_{max}}$$ HR max is often used to prescribe exercise intensities for training and rehabilitation. In the absence of maximal cardiopulmonary exercise testing (CPET), $$\mathrm {HR_{max}}$$ HR max and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max are typically estimated using traditional submaximal prediction methods with well-known limitations and inaccuracies. For this study, 12 regularly exercising healthy young adult males performed a bout of maximal CPET on a cycle ergometer to determine their true $$\mathrm {HR_{max}}$$ HR max and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max . Participants also performed a submaximal bout of exercise at varied intensities. A dynamical system model and heuristic parameter estimation algorithm were applied to the submaximal data to estimate the participants’ $$\mathrm {HR_{max}}$$ HR max and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max . The submaximal predictions were evaluated by computing the coefficient of determination $${R^2}$$ R 2 and the standard error of the estimate (SEE) through comparisons with the true maximal values for $$\mathrm {HR_{max}}$$ HR max ( $${R^2 = 0.96}$$ R 2 = 0.96 , SEE = 2.4 bpm) and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max ( $${R^2 = 0.93}$$ R 2 = 0.93 , SEE = 2.1 mL kg $$^{-1}$$ - 1  min $$^{-1}$$ - 1 ). The results from this study suggest that a dynamical system model and heuristic parameter estimation algorithm can provide accurate predictions for $$\mathrm {HR_{max}}$$ HR max and $$\dot{\mathrm {V}}{\mathrm {O_{2max}}}$$ V ˙ O 2 max using data collected from a submaximal testing protocol.

Journal

Sports Engineering – Springer Journals

Published: Jul 15, 2017

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