A mathematical model for predicting HR max, VO2 max, and oxygen uptake kinetics during treadmill walking and running at varied intensities Public Deposited
- Last Modified
- March 20, 2019
- Creator
-
Borror, Andrew
- Affiliation: College of Arts and Sciences, Department of Exercise and Sport Science
- Abstract
- Maximal oxygen uptake (VO2 max) is difficult to measure and most predictions are inaccurate due to a variety of assumptions. The purpose of this study was to validate a dynamical system model (DSM) for predicting HR max and VO2 max during walking and running. A secondary purpose was to predict VO2 responses using a neural network. Twenty-six healthy males completed a maximal cardiopulmonary exercise test (CPET) and a submaximal protocol. The models were applied to the submaximal data to estimate the participants’ HR/VO2 responses and predict their HR max and VO2 max. The model accurately tracked HR and VO2 responses (R2 = -.85-0.99). However, it did not accurately estimate max (R2 < 0). Further refinement of the model is needed. This study elucidated some of the challenges of using a DSM and demonstrated that a neural network may be useful for easily predicting VO2 responses.
- Date of publication
- May 2018
- Keyword
- DOI
- Resource type
- Rights statement
- In Copyright
- Advisor
- Battaglini, Claudio
- Mann, Brian
- Shields, Edgar
- Degree
- Master of Arts
- Degree granting institution
- University of North Carolina at Chapel Hill Graduate School
- Graduation year
- 2018
- Language
- Parents:
This work has no parents.
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Borror_unc_0153M_17609.pdf | 2019-04-10 | Public |
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