Covid-19 detection using Cough Sound with Neural Networks

ABSTRACT

COVID-19 has already had a significant influence on our everyday lives and with the influx of patients infected with the newer emerging variants there arises a need for a quick, accurate, and remote mode of identification. Cough sounds can play a vital role in the identification of COVID-19 in individuals. They can be used as an important factor to determine if the person is infected by COVID-19 or not, even with the prior existence of a respiratory ailment. Hence, we focused on providing a widely accessible and scalable solution through the method of a real-time mode of detection of the 'COVID cough' via a machine learning model trained 'COVID cough' recorded dataset. Based on the input, the person is provided with the diagnosis after being assessed by the model. © 2022 IEEE.