MYSTETH—home-based heart monitoring

TL;DR

MySteth is a home-based heart monitoring tool using smartphones or stethoscopes and AI to detect heart murmurs and classify them accurately.

Contribution

MySteth introduces a hybrid CNN-LSTM model with LPC preprocessing for high-accuracy home-based heart sound classification.

Findings

MySteth achieved 92% accuracy in distinguishing normal heartbeats from murmurs.

It classified systolic and diastolic murmurs with 91% accuracy.

Systolic murmurs were further categorized into ESM and PSM with 90% accuracy.

Abstract

The MySteth is an intelligent medical tool designed for cardiac disease screening, utilizing either a stethoscope or smartphone to record heart sounds. Normal heart sounds in healthy individuals consist of “lub” and “dub” noises, while murmurs—additional sounds during heartbeats—can indicate cardiac anomalies such as valve dysfunctions and rapid blood flow, categorized as systolic or diastolic.

MySteth was developed and tested using heart sounds recorded via smartphone and digital stethoscope. For ensuring the clinical validity of the data, all heart sound samples were meticulously annotated by human experts—super-specialized cardiologists with extensive experience in cardiac diagnostics. To achieve high classification accuracy, MySteth employs a hybrid CNN-LSTM model combined with Linear Predictive Coding (LPC) for preprocessing. The study involves classifying recorded heart sounds into normal heartbeats and murmurs, with murmurs further divided into systolic and diastolic categories.

The tool demonstrated an accuracy of 92% in distinguishing normal heartbeats from murmurs, 91% in classifying murmurs into systolic and diastolic types, and 90% in further categorizing systolic murmurs into Ejection Systolic Murmurs (ESM) and Pansystolic Murmurs (PSM). MySteth is accessible and affordable, requiring minimal equipment, as most individuals already own a smartphone, and digital stethoscopes are commonly available. This ease of use facilitates both professional and home-based heart monitoring, especially beneficial in remote areas with limited healthcare access.

MySteth is an at-home heart diagnostic tool that leverages deep learning to classify heart sounds into normal, ESM, PSM, and diastolic murmurs. Its user-friendly design and minimal hardware requirements ensure broad adoption across various healthcare settings, facilitating timely and accurate preliminary heart investigations. This capability is crucial in combating the global burden of cardiovascular diseases. MySteth's scalability and ease of deployment underscore its potential in early cardiovascular disease diagnosis, particularly in underserved regions, thereby promoting preventive healthcare.

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