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

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.