Utilization of Low-Cost Sound Sensors with a built in Microphone as a Respiratory Pattern Sound Indicator and a Risk Mitigation Tool

In response to COVID-19

Abstract

Since the detection of pattern abnormalities may lead to not only the prevention of chronic respiratory diseases but also other diseases, many techniques have been developed in order to detect breathing and coughing patterns. To benefit from the cross-disciplinary studies we have decided to expose physics students to both: learning about sound using coughing as a targeted research topic and to develop a demo tool that is useful for building on exploratory skills and provides them with solid knowledge for future more advanced scientific research in biomedical engineering. A low-cost microphone sensor was tested for the purpose of understanding whether it can be used not only as a sound indicator but more broadly as a risk mitigation tool during a pandemic such as the current pandemic, COVID-19. The final goal of this long-term project is to build mathematical models aiding the identification of features from sound samples and to apply a classifier algorithm based on the machine learning technique at the final stage of research.