Segmentation and time-frequency analysis of pathological Heart Sound Signals using the EMD method

The Phonocardiogram (PCG) is the graphical representation of acoustic energy due to the mechanical cardiac activity. Sometimes cardiac diseases provide pathological murmurs mixed with the main components of the Heart Sound Signal (HSs). The Empirical Mode Decomposition (EMD) allows decomposing a multicomponent signal into a set of monocomponent signals, called Intrinsic Mode Functions (IMFs). Each IMF represents an oscillatory mode with one instantaneous frequency. The goal of this paper is to segment some pathological HSs by selecting the most appropriate IMFs using the correlation coefficient. Then we extract some time-frequency characteristics considered as useful parameters to distinguish different cases of heart diseases. The experimental results conducted on some real-life pathological HSs such as: Mitral Regurgitation (MR), Aortic Regurgitation (AR) and the Opening Snap (OS) case; revealed the performance of the proposed method.