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A Convolution Model for Heart Rate Prediction in Physical Exercise

  • 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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Metadaten
Document Type:Conference Object
Language:English
Parent Title (English):Correia, Cabri (Eds.): Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support (icSPORTS 2016). November 7-9, 2016, in Porto, Portugal
First Page:157
Last Page:164
ISBN:978-989-758-205-9
DOI:https://doi.org/10.5220/0006030901570164
Publisher:SciTePress
Publication year:2016
Tag:Heart Rate Prediction; Predictive Models; Training Optimization
Departments, institutes and facilities:Fachbereich Informatik
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2016/12/02