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Segmentation of Pathological Heart Sound Signal Using Empirical Mode Decomposition

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.
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Submitted on : Wednesday, January 16, 2013 - 4:18:03 PM
Last modification on : Thursday, June 17, 2021 - 3:46:12 AM


  • HAL Id : hal-00777026, version 1



Daoud Boutana, Braham Barkat, Messaoud Benidir. Segmentation of Pathological Heart Sound Signal Using Empirical Mode Decomposition. ICSPS 2012, Dec 2012, Kuala Lumpur, Malaysia. pp.1-5. ⟨hal-00777026⟩



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