A Comprehensive Survey of Analysis of Heart Sounds using Machine Learning Techniques to Detect Heart Diseases

Main Article Content

S.Sathyanarayanan
Srikanta Murthy
Sanjay Chitnis

Keywords

congenital heart disease, computer-aided auscultation, deep learning, machine learning, heart sound auscultation, cardiovascular heart disease

Abstract

An estimated 32 per cent of all global deaths were due to cardiovascular diseases (CVD) in 2019 which is a leading cause of death globally. Of these, three-fourths of the deaths occur in low and middle-income nations. The CVD must be detected early for improving patient outcome. Automated heart sound analysis has been studied for more than a few decades using various Digital Signal Processing (DSP) techniques. Attempts have been made in the last decade to apply Machine Learning (ML) in the healthcare domain to make healthcare more accessible. This paper surveys the significant steps that have been taken to detect the most common heart diseases by the application of the machine learning (ML) and deep learning (DL) techniques to analyse the phonocardiograms over the last few years.

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