Heart sound classification plays a vital role in the early detection of cardiovascular disorders,
especially for small primary health care clinics. Despite that much progress has been made …

In the past few decades, analysis of heart sound signals (ie the phonocardiogram or PCG),
especially for automated heart sound segmentation and classification, has been widely …

The identification of the exact positions of the first and second heart sounds within a
phonocardiogram (PCG), or heart sound segmentation, is an essential step in the automatic …

Objective: This study focuses on the first (S1) and second (S2) heart sound recognition
based only on acoustic characteristics; the assumptions of the individual durations of S1 and …

Accurate measurement of heart sound and murmur parameters is of great importance in the
automated analysis of phonocardiogram (PCG) signals. In this paper, we propose a novel …

An efficient heart sound segmentation (HSS) method that automatically detects the location
of first (S 1) and second (S 2) heart sound and extracts them from heart auscultatory raw …

Objective: In this paper, we accurately detect the state-sequence first heart sound (S1)-
systole-second heart sound (S2)-diastole, ie, the positions of S1 and S2, in heart sound …

This paper presents a new module for heart sounds segmentation based on S-transform.
The heart sounds segmentation process segments the PhonoCardioGram (PCG) signal into …

Objective: This paper proposes a novel framework for the segmentation of phonocardiogram
(PCG) signals into heart states, exploiting the temporal evolution of the PCG as well as …

This paper studies the use of deep convolutional neural networks to segment heart sounds
into their main components. The proposed methods are based on the adoption of a deep …