Model based on support vector machine for the estimation of the heart rate variability

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 kn...

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Autores:

Tipo de recurso:

Fecha de publicación:

2018

Institución:

Universidad del Rosario

Repositorio:

Repositorio EdocUR - U. Rosario

Idioma:

eng

OAI Identifier:

oai:repository.urosario.edu.co:10336/22528

Acceso en línea:

https://doi.org/10.1007/978-3-030-01421-6_19
https://repository.urosario.edu.co/handle/10336/22528

Palabra clave:

Internet of things
Neural networks
Patient monitoring
Support vector machines
Application-oriented
Cardiac signals
Heart rate variability
Heart-rate monitors
Internet of Things (IOT)
Model-based OPC
Physical training
Support vector machine algorithm
Heart
Heart Rate Monitor (HRM)
Heart rate variability (HRV)
Internet of things (IOT)
Support vector machine (SVM)

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