Detection of COVID-19 infection based on electronic nose technique: preliminary study

Abstract

The coronavirus COVID-19 pandemic have reached almost every country in the world and caused a global health crisis. It is necessary to detect COVID-19 with fast and accurate diagnosis method in order to prevent the rapid spread of Covid-19. This paper presents a preliminary study of using electronic nose (e-nose) technology for detection of COVD-19 infection. In this experiment, the human exhaled breaths of healthy volunteers, asymptomatic and symptomatic COVID-19 patients were collected with commercial face masks for 5 minutes followed by the measurement with an e-nose machine in a closed system. The COVID-19 positivity was confirmed by RT-PCR method. According to the experiment, the odor intensity of human exhaled breath can be described with the total sensing response value. The exhaled breath of COVID-19 infected patients show higher odor intensity than the healthy volunteers (control). The Principal Component Analysis (PCA) shows the classification of three data groups; healthy volunteers, COVID-19 infected patients and unclassified people. For the unclassified cases, the medical record has shown that these people have been subjected either to some respiratory diseases or just recovered from COVID-19 infection. From these preliminary results, e-nose technology and its measurement proto-cols can be considered as a viable tool for COVID-19 rapid detection.