Digital Stethoscope For Instant Monitoring For Cardiac Auscultation

Abstract

The main problem that often arises for doctor is using stethoscope to detect lung sounds. The analysis of lung sound obtained by a stethoscope is challenging when the signal level is extremely low. As a consequence, the current acoustic stethoscope has to be replaced by a digital electronic stethoscope. The primary goal of this study is to design a digital stethoscope that monitor lungs sounds and identify potential illnesses using CNN model. The notification of the detected disease is sent by pushover application and graphical representation is shown in the THINKSPEAK application. Based on the analysis of the CNN model, the lung disease detection method achieved an average accuracy of 95%, which means it could be applied to diagnosis of lung disease in the real world.