Abstract—The Phonocardiogram (PCG) is the graphical recording of acoustic energy produced by the mechanical activity of various cardiac. Due to the complicated mechanisms involved in the generation of in the PCG signal, it is considered as multicomponent non stationary signal. Empirical mode decomposition (EMD) allows decomposing an observed multicomponent signal into a set of monocomponent signals, called Intrinsic Mode Functions (IMFs). The goal of this paper is to segment some pathological HS signals into the murmurs related to cardiac diseases. EMD approach allows to automatically selecting the most appropriate IMFs characterizing the murmur using the noise only model. Real-life signals are used in the various cases such as Early Aortic Stenosis (EAS), Late Aortic Stenosis (LAS), Mitral Regurgitation (MR) and Aortic Regurgitation (AR) to validate, and demonstrate the effectiveness of the proposed method.

Index Terms—Empirical mode decomposition, heart sound signal, pathological murmurs, noise only model.

D. Boutana is with the Department of Automatic, faculty of science and technology, university of Jijel Algeria (e-mail daoud.boutana@mail.com).
B. Barkat is with the Department of Electrical Engineering, Thepetroleum Institute, Abu Dhabi, United Arab Emirates (e-mail:bbarkat@pi.ac.ae ).
M. Benidir is with the Laboratoire des signaux et systèmes, supelec,université Paris-Sud, 91192 Gif sur-Yvette, France (e-mail :benidir@LSS.supelec.fr ).

Cite: Daoud Boutana, Braham Barkat, and Messaoud Benidir, "Segmentation of Pathological Heart Sound Signal Using Empirical Mode Decomposition," International Journal of Computer and Electrical Engineering vol. 5, no. 1, pp. 26-29, 2013.