Document Detail


Analysis of phonocardiogram signals using wavelet transform.
MedLine Citation:
PMID:  22738192     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Phonocardiograms (PCG) are recordings of the acoustic waves produced by the mechanical action of the heart. They generally consist of two kinds of acoustic vibrations: heart sounds and heart murmurs. Heart murmurs are often the first signs of pathological changes of the heart valves, and are usually found during auscultation in primary health care. Heart auscultation has been recognized for a long time as an important tool for the diagnosis of heart disease, although its accuracy is still insufficient to diagnose some heart diseases. It does not enable the analyst to obtain both qualitative and quantitative characteristics of the PCG signals. The efficiency of diagnosis can be improved considerably by using modern digital signal processing techniques. Therefore, these last can provide useful and valuable information on these signals. The aim of this study is to analyse PCG signals using wavelet transform. This analysis is based on an algorithm for the detection of heart sounds (the first and second sounds, S1 and S2) and heart murmurs using the PCG signal as the only source. The segmentation algorithm, which separates the components of the heart signal, is based on denoising by wavelet transform (DWT). This algorithm makes it possible to isolate individual sounds (S1 or S2) and murmurs. Thus, the analysis of various PCGs signals using wavelet transform can provide a wide range of statistical parameters related to the phonocardiogram signal.
Authors:
F Meziani; S M Debbal; A Atbi
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-6-28
Journal Detail:
Title:  Journal of medical engineering & technology     Volume:  -     ISSN:  1464-522X     ISO Abbreviation:  -     Publication Date:  2012 Jun 
Date Detail:
Created Date:  2012-6-28     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7702125     Medline TA:  J Med Eng Technol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Genie Biomedical Laboratory (GBM), Faculty of Technology, University A. B. Belkaid-Tlemcen BP 119 , Tlemcen , Algeria.
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