Towards the Implementation of Smartphone-Based Self-testing of COVID-19 Using AI

Abstract

The new type of coronavirus COVID-19 has widely spread in most of the world and causing a pandemic according to the World Health Organization (WHO). Many mechanisms to detect the coronavirus disease COVID-19 are used like clinical analysis of chest CT scan images and blood test results. Several methods can be used to detect the presence of Covid-19 such as medical detection Kits. Though, such devices require huge costs and it takes time to install and use. In addition to that, the negatively diagnosed patients consume many of the needed resources and space in hospitals that could be used by other patients having higher chance of being infected. In this paper, a new framework is proposed to detect COVID-19 using built-in smartphone sensors. The proposal provides a low-cost solution, since most of radiologists have already held smartphones for different daily purposes. Not only that but also ordinary people can use the framework on their smartphones for the virus detection purposes. Nowadays, almost every household possesses at least one smartphone with powerful processors and advanced sensors. By combining the data collected by the various sensors, such as temperature data, coughing and breathing recording with questionnaires about the background of the phone user, artificial intelligence (AI) and advanced signal processing tools may analyze the recorded data in order to produce viable diagnosis of Covid-19 infection, and hence alleviate the ongoing pressure on the health system (hospitals and stuff).