Method for monitoring vital signs, in online classes, using low-cost devices, for student health care, in times of the COVID-19 pandemic

• Autores: Auccahuasi Aiquipa, Wilver, Pando Ezcurra, Tamara, Herrera Mejía, Zoran Evaristo, Bejarano Álvarez, Patricia Mónica, Herrera Ugarte, Lucas
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad Privada Peruano Alemana
• Repositorio: UPAL - Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.upal.edu.pe:20.500.14107/64
• Enlace del recurso: https://hdl.handle.net/20.500.14107/64
• Nivel de acceso: acceso abierto
• Materia: Nivel de oxígeno; Frecuencia cardíaca; Aprendizaje en línea; Equipos de medición; Oxygen level; Heart rate; Electronic learning; Measurement equipment; https://purl.org/pe-repo/ocde/ford#5.03.01

In times of pandemic caused by the COVID-19 pandemic, many of the activities we carry out on a daily basis are changing; education is one of them, mainly affecting school-age children, the changes that are occurring, caused by voluntary confinement, the purpose of this publication is related to the presentation of a method to be able to register, measure and monitor oxygen saturation levels and heart rate, when children are taking their classes online; the contribution and contribution of the results will allow evaluating changes in the behavior of the respiratory system, caused by some factors of confinement, by presenting stress and in some cases by the same effects of the coronavirus, the method proposes the use of well-known smart watches , which have the advantage of being able to non-invasively measure oxygen saturation and heart rate, these values ​​can be displayed on the watch itself, as well as being able to record the values ​​through an application on mobile devices, such as cell phones. To obtain the results, the method was applied to a group of 15 students of different ages, where the registration and measurements were made, demonstrating that the method is practical in its implementation and in being able to analyze the data, demonstrating that it can be very useful to know as it is the behavior of the variables mainly when they are in their online classes and their effects that they can cause, the proposed method can be scalable depending on the needs and applications.