Remote and non-invasive monitoring of patients with COVID-19 by smartphone

The pandemic caused by the new coronavirus (SARS-COV-2) has led to more than two million deaths in the world by March 2021. The worldwide call to reduce transmission is enormous. Recently, there has been a rapid growth of telemedicine and the use of mobile health (mHealth) in the context of the COVI...

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Detalles Bibliográficos
Autores: Mazzu-Nascimento, Thiago, Nogueira Evangelista, Danilo, Abubakar, Obeedu, Geraldo Alves Souto, Bernardino, Domingues, Lucas Vinicius, Furtado Silva, Diego, Nogueira-de-Almeida , Carlos Alberto
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:Brasil
Institución:Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)
Repositorio:Scientia Medica (Porto Alegre. Online)
Idioma:inglés
OAI Identifier:oai:ojs.revistaseletronicas.pucrs.br:article/39340
Acceso en línea:https://revistaseletronicas.pucrs.br/scientiamedica/article/view/39340
Access Level:acceso abierto
Palabra clave:coronavirus infections
mobile health
pandemics
smartphone
telemedicine
infecções por Coronavirus
saúde móvel
pandemia,
telemedicina
Descripción
Sumario:The pandemic caused by the new coronavirus (SARS-COV-2) has led to more than two million deaths in the world by March 2021. The worldwide call to reduce transmission is enormous. Recently, there has been a rapid growth of telemedicine and the use of mobile health (mHealth) in the context of the COVID-19 pandemic. Smartphone accessories such as a flashlight, camera, microphone, and microprocessor can measure different clinical parameters such as oxygen saturation, blood pressure, heart rate, breathing rate, fever, pulmonary auscultation, and even voice analysis. All these parameters are of great clinical importance when evaluating suspected patients of COVID-19 or monitoring infected patients admitted in various hospitals or in-home isolation. In remote medical care, the results of these parameters can be sent to a call center or a health unit for interpretation by a qualified health professional. Thus, the patient can receive orientations or be immediately referred for in-patient care. The application of machine learning and other artificial intelligence strategies assume a central role in signal processing and are gaining much space in the medical field. In this work, we present different approaches for evaluating clinical parameters that are valuable in the case of COVID-19 and we hope that soon all these parameters can be measured by a single smartphone application, facilitating remote clinical assessments.