A Novel AI-enabled Framework to Diagnose Coronavirus COVID-19 using Smartphone Embedded Sensors: Design Study

Abstract

Coronaviruses are a famous family of viruses that cause illness in both humans and animals. The new type of coronavirus COVID-19 was firstly discovered in Wuhan, China. However, recently, the virus has widely spread in most of the world and causing a pandemic according to the World Health Organization (WHO). Further, nowadays, all the world countries are striving to control the COVID-19. There are many mechanisms to detect coronavirus including clinical analysis of chest CT scan images and blood test results. The confirmed COVID-19 patient manifests as fever, tiredness, and dry cough. Particularly, several techniques can be used to detect the initial results of the virus such as medical detection Kits. However, such devices are incurring huge cost, taking time to install them and use. Therefore, 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 dailypurposes. Not only that but also ordinary people can use the framework on their smartphones for the virus detection purposes. Today's smartphones are powerful with existing computationrich processors, memory space, and large number of sensors including cameras, microphone, temperature sensor, inertial sensors, proximity, colour-sensor, humidity-sensor, and wireless chipsets/sensors. The designed Artificial Intelligence (AI) enabled framework reads the smartphone sensors' signal measurements to predict the grade of severity of the pneumonia as well as predicting the result of the disease.

COVID-19 diagnosis —A review of current methods

“…Although the sensitivity is still a question, such systems can be useful to monitor and act on mass populations worldwide online. Maghdid et al (2020b) An electrical probe to detect COVID-19 spike protein S1 Receptor Binding Domain-modified graphene field-effect transistor was used to identify spike proteins The sensor can capture S1 protein at a limit of detection down to 0.2 pM, in a real-time and label-free manner. The platform could also be used to screen high-affinity antibodies.…”

Can AI help in the fight against COVID ‐19?

“…Data from phone hotlines used to pre‐screen individuals based on travel history and symptoms,16 and from sensors (cameras, microphones, temperature and inertial sensors) embedded within smartphones, can all be used to detect COVID‐19 17. Neural networks embedded in cameras can distinguish patterns of tachypnoea caused by COVID‐19 from those caused by influenza or the common cold 18.…”

Detection of nCoV-19 from Hybrid Dataset of CXR Images using Deep Convolutional Neural Network

“…It was claimed that both Chest X-rays (CXR) and Computed Tomography (CT) scans can be used for COVID-19 detection built on AI modeling. The scholars also proposed that CT images for the identification of COVID-19 should be scanned using a cell phone [10].…”