M-health system for cardiac and COVID patient monitoring using body sensor networks and machine learning

Francisco Beltrán-Chávez; Félix Mata-Rivera; Mario Rivero; Roberto Zagal-Flores; Giovanni Guzmán; Rolando Quintero; Miguel Torres-Ruiz

doi:10.1016/B978-0-12-821318-6.00011-6

M-health system for cardiac and COVID patient monitoring using body sensor networks and machine learning

Francisco Beltrán-Chávez, Félix Mata-Rivera, Mario Rivero, Roberto Zagal-Flores, Giovanni Guzmán, Rolando Quintero, Miguel Torres-Ruiz

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

The COVID-19 pandemic has promoted the need to take care of health at home, using M-Health systems to monitor vital signs in healthy people and in those with heart conditions. Thus, the body sensor networks (BSNs) are extremely useful for sensing and alerting when some type of health risk is identified such as arrhythmia and low oxygen levels as well as for helping to make a decision. This chapter describes a home health monitoring system to identify cardiac risk events and monitor oxygenation levels in a person using a BSN simulator and exploring the energy performance of the network, considering the IoT devices installed at home. The work is oriented toward monitoring and identifying risk events in closed spaces, and it is addressed to people with two types of conditions: (1) those with heart diseases and (2) those people who need to monitor their oxygen levels after recovering from the COVID-19 disease.

Original language	English
Title of host publication	Digital Innovation for Healthcare in COVID-19 Pandemic
Subtitle of host publication	Strategies and Solutions
Publisher	Elsevier
Pages	217-244
Number of pages	28
ISBN (Electronic)	9780128213186
ISBN (Print)	9780128232101
DOIs	https://doi.org/10.1016/B978-0-12-821318-6.00011-6
State	Published - 1 Jan 2022

Keywords

Arrhythmia detection
Body sensor network
COVID-19 disease
Energy measurement protocol
IoT devices
Machine learning
Mobile devices
Neural network classifier
Sensor data integration
Smart healthcare

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10.1016/B978-0-12-821318-6.00011-6

Cite this

Beltrán-Chávez, F., Mata-Rivera, F., Rivero, M., Zagal-Flores, R., Guzmán, G., Quintero, R., & Torres-Ruiz, M. (2022). M-health system for cardiac and COVID patient monitoring using body sensor networks and machine learning. In Digital Innovation for Healthcare in COVID-19 Pandemic: Strategies and Solutions (pp. 217-244). Elsevier. https://doi.org/10.1016/B978-0-12-821318-6.00011-6

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Beltrán-Chávez, F, Mata-Rivera, F, Rivero, M, Zagal-Flores, R , Guzmán, G , Quintero, R & Torres-Ruiz, M 2022, M-health system for cardiac and COVID patient monitoring using body sensor networks and machine learning. in Digital Innovation for Healthcare in COVID-19 Pandemic: Strategies and Solutions. Elsevier, pp. 217-244. https://doi.org/10.1016/B978-0-12-821318-6.00011-6

M-health system for cardiac and COVID patient monitoring using body sensor networks and machine learning. / Beltrán-Chávez, Francisco; Mata-Rivera, Félix; Rivero, Mario et al.
Digital Innovation for Healthcare in COVID-19 Pandemic: Strategies and Solutions. Elsevier, 2022. p. 217-244.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Guzmán, Giovanni

AU - Quintero, Rolando

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M-health system for cardiac and COVID patient monitoring using body sensor networks and machine learning

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Keywords

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