Healthcare Technology

B N M Institute of Technology



The present pandemic COVID-19 major impact is on the lungs of the human being which reduces the breathing rate and oxygen intake, CT scan are best preferred by doctor to assist and identify COVID-19 stage or pneumonia in the people. In this paper a novel approach has been proposed to identify the lung abnormality through the sounds generated by the air when it travels through the respiratory organ of the human.
To assess the condition of the lungs in this method sound wave analysis is done by evaluating the audio diagnostics of the lungs which is recorded through sensors and modified stethoscope chest pieces. Hence the process used is a non-invasive one which would be cost effective and can be easily used by any layman. In this paper a sound wave analysis is done on the sound captured through stethoscope. Stethoscope captures the sound of the lungs, heart beat and the external noise.
Random forest supervised machine learning algorithm is used to classify normal and abnormal lungs. Trained and tested the model with the help of Kaggle data set.

Project Team

Sathwik C Gowda, Tejas S Koundinya
Computer Science Engineering


Dr. Chayadevi
B N M Institute of Technology
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