Physiological Parameters-Based Mobile and Non-Contact COVID-19 Screening System Using RGB-Depth-Thermal Cameras

Abstract

In this paper, we design and develop a vital signs-based mobile medical screening system using cameras (MMSS) to detect possible COVID-19 infection in a non-contact way. The MMSS utilizes different types of cameras, including red-green-blue, depth, and thermal cameras, to measure physiological parameters such as heart rate (HR), respiration rate (RR), and body temperature (BT) in order to detect the infection. We proposed body movement reduction and measurement condition assessment algorithms to acquire reliable physiological signals. Also, we proposed a pixel translation-based computation cost-effective method for setting multiple regions of interest for the cameras’ images. The MMSS-obtained HR, RR, and BT measurement results and the references were correlated significantly with correlation coefficients of 0.97, 0.93, and 0.72, respectively. In clinical testing, the MMSS demonstrated 91% sensitivity and 90% specificity for screening COVID-19 infection.