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

Keywords: coronavirus infections, mobile health, pandemics, smartphone, telemedicine

Abstract

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.

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Author Biographies

Thiago Mazzu-Nascimento, Federal University of São Carlos (UFSCar), Department of Medicine, São Carlos, SP, Brazil.

BSc in Biomedicine, Ph.D. in Chemistry from the Institute of Chemistry of São Carlos (IQSC) at University of São Paulo (USP), São Carlos, SP, Brazil. Undergraduate medical student and Postdoctoral researcher in Computer Science from the Federal University of São Carlos (UFSCar), São Carlos, SP, Brazil.

Danilo Nogueira Evangelista, Federal University of São Carlos (UFSCar), Department of Medicine, São Carlos, SP, Brazil.

BSc in Biomedicine. Undergraduate medical student from the Federal University of São Carlos (UFSCar), São Carlos, SP, Brazil.

Obeedu Abubakar, Federal University of São Carlos (UFSCar), Department of Medicine, São Carlos, SP, Brazil.

Undergraduate medical student from the Federal University of São Carlos (UFSCar), São Carlos, SP, Brazil.

Bernardino Geraldo Alves Souto, Federal University of São Carlos (UFSCar), Department of Medicine, São Carlos, SP, Brazil.

M.D from Federal University of Juiz de Fora (UFJF), Juiz de Fora, MG, Brazil. Master of Tropical Medicine, Ph.D. in Infectious Diseases and Tropical Medicine from Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil. Post-Doctorate fellow in Microbiology and Infection from University of Minho, Braga, Portugal. Associate professor in the department of medicine from the Federal University of São Carlos (UFSCar), São Carlos, SP, Brazil.

Lucas Vinicius Domingues, Federal University of São Carlos (UFSCar), Department of Computing, São Carlos, SP, Brazil.

Undergraduate in Computer Science from the Federal University of São Carlos (UFSCar), São Carlos, SP, Brazil.

Diego Furtado Silva, Federal University of São Carlos (UFSCar), Department of Computing, São Carlos, SP, Brazil.

BSc, Master, and Ph.D. in Computer Science from Institute of Mathematical and Computer Sciences (ICMC) at University of São Paulo (USP), São Carlos, SP, Brazil. Adjunct professor in the Department of Computer Science from the Federal University of São Carlos (UFSCar), São Carlos, SP, Brazil.

Carlos Alberto Nogueira-de-Almeida, Federal University of São Carlos (UFSCar), Department of Medicine, São Carlos, SP, Brazil.

M.D from University of São Paulo (USP), Master and Ph.D. in pediatrics from University of São Paulo (USP), Ribeirão Preto, SP, Brazil. Director of the Department of Pediatric Nutrology of the Brazilian Association of Nutrology. Adjunct professor in the department of medicine from the Federal University of São Carlos (UFSCar), São Carlos, SP, Brazil.

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Published
2021-04-05
How to Cite
Mazzu-Nascimento, T., Nogueira Evangelista, D., Abubakar, O., Geraldo Alves Souto, B., Domingues, L. V., Furtado Silva, D. ., & Nogueira-de-Almeida , C. A. (2021). Remote and non-invasive monitoring of patients with COVID-19 by smartphone. Scientia Medica, 31(1), e39340. https://doi.org/10.15448/1980-6108.2021.1.39340