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Authors: Melanie Ludwig 1 ; Harald G. Grohganz 2 and Alexander Asteroth 1

Affiliations: 1 Bonn-Rhein-Sieg University o.A.S., Germany ; 2 Blue Square Group e.V., Germany

ISBN: 978-989-758-205-9

Keyword(s): Predictive Models, Heart Rate Prediction, Training Optimization.

Related Ontology Subjects/Areas/Topics: Computer Supported Training ; Computer Systems in Sports ; Health and Fitness ; Health, Sports Performance and Support Technology ; Simulation and Mathematical Modeling ; Sport Science Research and Technology

Abstract: During exercise, heart rate has proven to be a good measure in planning workouts. It is not only simple to measure but also well understood and has been used for many years for workout planning. To use heart rate to control physical exercise, a model which predicts future heart rate dependent on a given strain can be utilized. In this paper, we present a mathematical model based on convolution for predicting the heart rate response to strain with four physiologically explainable parameters. This model is based on the general idea of the Fitness-Fatigue model for performance analysis, but is revised here for heart rate analysis. Comparisons show that the Convolution model can compete with other known heart rate models. Furthermore, this new model can be improved by reducing the number of parameters. The remaining parameter seems to be a promising indicator of the actual subject’s fitness.

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Paper citation in several formats:
Ludwig M., G. Grohganz H. and Asteroth A. (2016). A Convolution Model for Heart Rate Prediction in Physical Exercise.In Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support - Volume 1: icSPORTS, ISBN 978-989-758-205-9, pages 157-164. DOI: 10.5220/0006030901570164

@conference{icsports16,
author={Melanie Ludwig and Harald G. Grohganz and Alexander Asteroth},
title={A Convolution Model for Heart Rate Prediction in Physical Exercise},
booktitle={Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support - Volume 1: icSPORTS,},
year={2016},
pages={157-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006030901570164},
isbn={978-989-758-205-9},
}

TY - CONF

JO - Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support - Volume 1: icSPORTS,
TI - A Convolution Model for Heart Rate Prediction in Physical Exercise
SN - 978-989-758-205-9
AU - Ludwig M.
AU - G. Grohganz H.
AU - Asteroth A.
PY - 2016
SP - 157
EP - 164
DO - 10.5220/0006030901570164

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