Autores
Mata Rivera Miguel Félix
Rivero Ángeles Mario Eduardo
Torres Ruiz Miguel Jesús
Zagal Flores Roberto Eswart
Guzmán Lugo José Giovanni
Quintero Téllez Rolando
Título M-health system for cardiac and COVID patient monitoring using body sensor networks and machine learning
Tipo Libro
Sub-tipo Indefinido
Descripción Digital Innovation for Healthcare in COVID-19 Pandemic: Strategies and Solutions
Resumen 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. © 2022 Elsevier Inc. All rights reserved.
Observaciones DOI 10.1016/B978-0-12-821318-6.00011-6
Lugar Amsterdam
País Paises Bajos
No. de páginas 217-244
Vol. / Cap.
Inicio 2022-01-01
Fin
ISBN/ISSN 9780128213186