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

Publication ,  Journal Article
Mazzoleni, MJ; Battaglini, CL; Martin, KJ; Coffman, EM; Ekaidat, JA; Wood, WA; Mann, BP
Published in: Sports Engineering
March 1, 2018

This study examines the viability of utilizing a dynamical system model and heuristic parameter estimation algorithm to make predictions for maximum heart rate (HR max) and maximal oxygen uptake (V ˙ O 2 max) using data collected from a submaximal testing protocol. V ˙ O 2 max is widely considered to be the best single measurement of overall fitness in humans. When a V ˙ O 2 max assessment is not available, HR max is often used to prescribe exercise intensities for training and rehabilitation. In the absence of maximal cardiopulmonary exercise testing (CPET), HR max and 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 HR max and 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’ HR max and V ˙ O 2 max. The submaximal predictions were evaluated by computing the coefficient of determination R2 and the standard error of the estimate (SEE) through comparisons with the true maximal values for HR max (R2= 0.96 , SEE = 2.4 bpm) and V ˙ O 2 max (R2= 0.93 , SEE = 2.1 mL kg- 1 min- 1). The results from this study suggest that a dynamical system model and heuristic parameter estimation algorithm can provide accurate predictions for HR max and V ˙ O 2 max using data collected from a submaximal testing protocol.

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Published In

Sports Engineering

DOI

EISSN

1460-2687

ISSN

1369-7072

Publication Date

March 1, 2018

Volume

21

Issue

1

Start / End Page

31 / 41

Related Subject Headings

  • 4207 Sports science and exercise
  • 1106 Human Movement and Sports Sciences
  • 0913 Mechanical Engineering
  • 0906 Electrical and Electronic Engineering
 

Citation

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Mazzoleni, M. J., Battaglini, C. L., Martin, K. J., Coffman, E. M., Ekaidat, J. A., Wood, W. A., & Mann, B. P. (2018). A dynamical systems approach for the submaximal prediction of maximum heart rate and maximal oxygen uptake. Sports Engineering, 21(1), 31–41. https://doi.org/10.1007/s12283-017-0242-1
Mazzoleni, M. J., C. L. Battaglini, K. J. Martin, E. M. Coffman, J. A. Ekaidat, W. A. Wood, and B. P. Mann. “A dynamical systems approach for the submaximal prediction of maximum heart rate and maximal oxygen uptake.” Sports Engineering 21, no. 1 (March 1, 2018): 31–41. https://doi.org/10.1007/s12283-017-0242-1.
Mazzoleni MJ, Battaglini CL, Martin KJ, Coffman EM, Ekaidat JA, Wood WA, et al. A dynamical systems approach for the submaximal prediction of maximum heart rate and maximal oxygen uptake. Sports Engineering. 2018 Mar 1;21(1):31–41.
Mazzoleni, M. J., et al. “A dynamical systems approach for the submaximal prediction of maximum heart rate and maximal oxygen uptake.” Sports Engineering, vol. 21, no. 1, Mar. 2018, pp. 31–41. Scopus, doi:10.1007/s12283-017-0242-1.
Mazzoleni MJ, Battaglini CL, Martin KJ, Coffman EM, Ekaidat JA, Wood WA, Mann BP. A dynamical systems approach for the submaximal prediction of maximum heart rate and maximal oxygen uptake. Sports Engineering. 2018 Mar 1;21(1):31–41.
Journal cover image

Published In

Sports Engineering

DOI

EISSN

1460-2687

ISSN

1369-7072

Publication Date

March 1, 2018

Volume

21

Issue

1

Start / End Page

31 / 41

Related Subject Headings

  • 4207 Sports science and exercise
  • 1106 Human Movement and Sports Sciences
  • 0913 Mechanical Engineering
  • 0906 Electrical and Electronic Engineering