Segmentation of Pathological Heart Sound Signal Using Empirical Mode Decomposition

Daoud Boutana Braham Barkat Messaoud Benidir 1
1 Division Signaux
L2S - Laboratoire des signaux et systèmes
Abstract : The Phonocardiogram (PCG) is the graphicalrecording of acoustic energy produced by the mechanicalactivity of various cardiac. Due to the complicated mechanismsinvolved in the generation of in the PCG signal, it is consideredas multicomponent non stationary signal. Empirical modedecomposition (EMD) allows decomposing an observedmulticomponent signal into a set of monocomponent signals,called Intrinsic Mode Functions (IMFs). The goal of this paperis to segment some pathological HS signals into the murmursrelated to cardiac diseases. EMD approach allows toautomatically selecting the most appropriate IMFscharacterizing the murmur using the noise only model. Real-lifesignals are used in the various cases such as Early AorticStenosis (EAS), Late Aortic Stenosis (LAS), MitralRegurgitation (MR) and Aortic Regurgitation (AR) to validate,and demonstrate the effectiveness of the proposed method.
Type de document :
Article dans une revue
International Journal of Computer and Electrical Engineering - IJCEE, 2013, 5 (1), pp.26-29. 〈10.7763/ijcee.2013.v5.655〉
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Contributeur : Myriam Baverel <>
Soumis le : mardi 18 février 2014 - 09:32:16
Dernière modification le : jeudi 11 janvier 2018 - 06:26:18

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Daoud Boutana, Braham Barkat, Messaoud Benidir. Segmentation of Pathological Heart Sound Signal Using Empirical Mode Decomposition. International Journal of Computer and Electrical Engineering - IJCEE, 2013, 5 (1), pp.26-29. 〈10.7763/ijcee.2013.v5.655〉. 〈hal-00948278〉

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