Cardiac auscultation is an essential part of physical examination and plays a key role in the
early diagnosis of many cardiovascular diseases. The analysis of phonocardiography (PCG) …

Heart failure and heart valvar diseases are chronic heart disorders which are potentially
diagnosed using heart sound characteristics. Heart sound components S1 and S2 exhibit …

Recently, we have proposed a deep learning based heart sound recognition framework,
which can provide high recognition performance under clean testing conditions. However …

Due to inherent non-linearity coupled homologous morphology of heart sounds,
distinguishable noise robust biomarkers are essential for segregation of phonocardiogram …

This work considers the problem of segmenting heart sounds into their fundamental
components. We unify statistical and data-driven solutions by introducing Markov-based …

In this paper we propose a cardiac biometric system for human identity verification based on
an automatic selection algorithm of the best subsequence of a DHS (digital heart sound) …

This paper addresses the estimation of systolic time intervals, namely the pre-ejection period
(PEP) and the left ventricular ejection time (LVET), using heart sound. PEP is estimated with …

Heart sound segmentation has been shown to improve the performance of artificial
intelligence (AI)-based auscultation decision support systems increasingly viewed as a …

Heart sound (HS) signals contain valuable diagnostic information for detection of heart
abnormalities. The early detection of heart abnormalities plays an important role in reducing …

There has been a sustained effort in the research community over the recent years to
develop algorithms that automatically analyze heart sounds. One of the major challenges is …