Analysis of phonocardiogram signals using wavelet transform

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2012

Erschienen:

2012

Enthalten in:

Zur Gesamtaufnahme - volume:36

Enthalten in:

Journal of medical engineering & technology - 36(2012), 6 vom: 27. Aug., Seite 283-302

Sprache:

Englisch

Beteiligte Personen:

Meziani, F [VerfasserIn]
Debbal, S M [VerfasserIn]
Atbi, A [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
Review

Anmerkungen:

Date Completed 29.10.2012

Date Revised 24.07.2012

published: Print-Electronic

Citation Status MEDLINE

doi:

10.3109/03091902.2012.684830

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM218969376