TY - GEN
T1 - Model Based on Support Vector Machine for the Estimation of the Heart Rate Variability
AU - Hernández-Ruiz, Catalina Maria
AU - Villagrán Martínez, Sergio Andrés
AU - Ortiz Guzmán, Johan Enrique
AU - Gaona Garcia, Paulo Alonso
PY - 2018/1/1
Y1 - 2018/1/1
N2 - This paper shows the design, implementation and analysis of a Machine Learning (ML) model for the estimation of Heart Rate Variability (HRV). Through the integration of devices and technologies of the Internet of Things, a support tool is proposed for people in health and sports areas who need to know an individual’s HRV. The cardiac signals of the subjects were captured through pectoral bands, later they were classified by a Support Vector Machine algorithm that determined if the HRV is depressed or increased. The proposed solution has an efficiency of 90.3% and it’s the initial component for the development of an application oriented to physical training that suggests exercise routines based on the HRV of the individual.
AB - This paper shows the design, implementation and analysis of a Machine Learning (ML) model for the estimation of Heart Rate Variability (HRV). Through the integration of devices and technologies of the Internet of Things, a support tool is proposed for people in health and sports areas who need to know an individual’s HRV. The cardiac signals of the subjects were captured through pectoral bands, later they were classified by a Support Vector Machine algorithm that determined if the HRV is depressed or increased. The proposed solution has an efficiency of 90.3% and it’s the initial component for the development of an application oriented to physical training that suggests exercise routines based on the HRV of the individual.
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U2 - 10.1007/978-3-030-01421-6_19
DO - 10.1007/978-3-030-01421-6_19
M3 - Conference contribution
AN - SCOPUS:85054845276
SN - 9783030014209
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 186
EP - 194
BT - Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, 2018, Proceedings
A2 - Manolopoulos, Yannis
A2 - Hammer, Barbara
A2 - Maglogiannis, Ilias
A2 - Kurkova, Vera
A2 - Iliadis, Lazaros
PB - Springer
T2 - 27th International Conference on Artificial Neural Networks, ICANN 2018
Y2 - 4 October 2018 through 7 October 2018
ER -