Electronic Nose With Detection Method for Alcohol, Acetone, and Carbon Monoxide in Coronavirus Disease 2019 Breath Simulation Model.

Abstract

Electronic nose technology may have the potential to substantially slow the spread of contagious diseases with rapid signal indication. As our understanding of infectious diseases such as Corona Virus Disease 2019 improves, we expect electronic nose technology to detect changes associated with pathogenesis of the disease such as biomarkers of immune response for respiratory symptoms, central nervous system injury, and/or peripheral nervous system injury in the breath and/or odor of an individual. In this paper, a design of an electronic nose was configured to detect the concentration of a COVID-19 breath simulation sample of alcohol, acetone, and carbon monoxide mixture. After preheating for 24 hours, the sample was carried into an internal bladder of the collection vessel for analysis and data was collected from three sensors to determine suitability of these sensors for the application of exhaled breath analysis. Test results show a detection range in parts-per-million within the sensor detection range of at least 10–300 ppm. The output response of an MQ-2 and an MQ-135 sensor to a diverse environment of target gasses show the MQ-2 taking a greater length of time to normalize baseline drift compared to an MQ-135 sensor due to cross interferences with other gasses. The COVID-19 breath simulation sample was established and validated based on preliminary data obtained from parallel COVID-19 breath studies based in Edinburgh and Dortmund. This detection method provides a non-invasive, rapid, and selective detection of gasses in a variety of applications in virus detection as well as agricultural and homeland security.