Literature DB >> 9691571

Analysis-synthesis of the phonocardiogram based on the matching pursuit method.

X Zhang1, L G Durand, L Senhadji, H C Lee, J L Coatrieux.   

Abstract

The matching pursuit method of Mallat and Zhang is applied to the analysis and synthesis of phonocardiograms (PCG's). The method is based on a classical Gabor wavelet or time-frequency atom which is the product of a sinusoid and a Gaussian window function. It decomposes a signal into a series of time-frequency atoms by an iterative process based on selecting the largest inner product of the signal (and the subsequent residues) with atoms from a redundant dictionary. The Gaussian window controls the envelope duration and time position of each atom; and the sinusoid represents the frequency. The method was applied to two sets of PCG's: one with very low-noise level and the other with 10% noise energy. Each data base includes 11 PCG's representing the normal and the pathological conditions of the heart. The normalized root-mean-square error (NRMSE) was computed between the original and the reconstructed signals. The results show that the matching pursuit method is very suitable to the transient and complex properties of the PCG's, as it yielded excellent NRMSE's around 2.2% for the two sets of 11 PCG's tested.

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Year:  1998        PMID: 9691571     DOI: 10.1109/10.704865

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  7 in total

1.  A dynamical model for generating synthetic Phonocardiogram signals.

Authors:  Ali Almasi; Mohammad B Shamsollahi; Lotfi Senhadji
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

2.  Haemodynamic determinants of the mitral valve closure sound: a finite element study.

Authors:  D R Einstein; K S Kunzelman; P G Reinhall; R P Cochran; M A Nicosia
Journal:  Med Biol Eng Comput       Date:  2004-11       Impact factor: 2.602

3.  Time-frequency scaling transformation of the phonocardiogram based of the matching pursuit method.

Authors:  X Zhang; L G Durand; L Senhadji; H C Lee; J L Coatrieux
Journal:  IEEE Trans Biomed Eng       Date:  1998-08       Impact factor: 4.538

4.  Backpropagation artificial neural network classifier to detect changes in heart sound due to mitral valve regurgitation.

Authors:  Rakesh Kumar Sinha; Yogender Aggarwal; Barda Nand Das
Journal:  J Med Syst       Date:  2007-06       Impact factor: 4.460

5.  Analysis of the first heart sound using the matching pursuit method.

Authors:  W Wang; Z Guo; J Yang; Y Zhang; L G Durand; M Loew
Journal:  Med Biol Eng Comput       Date:  2001-11       Impact factor: 3.079

6.  Signal processing of heart signals for the quantification of non-deterministic events.

Authors:  Véronique Millette; Natalie Baddour
Journal:  Biomed Eng Online       Date:  2011-01-26       Impact factor: 2.819

7.  Detection of the valvular split within the second heart sound using the reassigned smoothed pseudo Wigner-Ville distribution.

Authors:  Abdelghani Djebbari; Fethi Bereksi-Reguig
Journal:  Biomed Eng Online       Date:  2013-04-30       Impact factor: 2.819

  7 in total

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