TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Ludwig, Melanie
A1  - Sundaram, Ashok Meenakshi
A1  - Füller, Matthias
A1  - Asteroth, Alexander
A1  - Prassler, Erwin
T1  - On modeling the cardiovascular system and predicting the human heart rate under strain
T2  - Proceedings of the 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AgingWell), May 20-22, 2015, in Lisbon, Portugal
N2  - With the increasing average age of the population in many developed countries, afflictions like cardiovascular diseases have also increased. Exercising has a proven therapeutic effect on the cardiovascular system and can counteract this development. To avoid overstrain, determining an optimal training dose is crucial. In previous research, heart rate has been shown to be a good measure for cardiovascular behavior. Hence, prediction of the heart rate from work load information is an essential part in models used for training control. Most heart-rate-based models are described in the context of specific scenarios, and have been evaluated on unique datasets only. In this paper, we conduct a joint evaluation of existing approaches to model the cardiovascular system under a certain strain, and compare their predictive performance. For this purpose, we investigated some analytical models as well as some machine learning approaches in two scenarios: prediction over a certain time horizon into the future, and estimation of the relation between work load and heart rate over a whole training session.
Y1  - 2015
SN  - 978-989-758-102-1
SB  - 978-989-758-102-1
U6  - https://doi.org/10.5220/0005449001060117
DO  - https://doi.org/10.5220/0005449001060117
SP  - 106
EP  - 117
PB  - SciTePress
ER  -