Abstract

The presence of abnormal sounds in one cardiac cycle, provide valuable information on various diseases.Early detection of various diseases is necessary; it is done by a simple technique known as: phonocardiography. The phonocardiography, based on registration of vibrations or oscillations of different frequencies, audible or not, that correspond to normal and abnormal heart sounds. It provides the clinician with a complementary tool to record the heart sounds heard during auscultation. The advancement of intracardiac phonocardiography, combined with signal processing techniques, has strongly renewed researchers’ interest in studying heart sounds and murmurs. This paper presents an algorithm based on the denoising by wavelet transform (DWT) and the Shannon energy of the PCG signal, for the detection of heart sounds (the first and second sounds, S1 and S2) and heart murmurs. This algorithm makes it possible to isolate individual sounds (S1 or S2) and murmurs to give an assessment of their average duration.

Highlights

  • Noninvasive diagnosis, such as phonocardiogram (PCG), offers useful information of functioning heart

  • This paper presents an algorithm based on the denoising by wavelet transform (DWT) and the Shannon energy of the PCG signal, for the detection of heart sounds and heart murmurs

  • This document present an algorithm for segmenting the phonocardiogram signal based on wavelet denoising

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Summary

Introduction

Noninvasive diagnosis, such as phonocardiogram (PCG), offers useful information of functioning heart. The PCG signal needs to be segmented into components (sounds or murmurs), and the components are analyzed separately. The oldest ones are based on the Fourier Transform (FT), which produces an average spectrum over time. This is can be suitable for signals whose statistical properties are invariant over time "stationary". The Short-term Fourier transform (STFT) is one of the oldest methods that are used to analysis biomedical signal. It may not allow good resolution in time andfrequencysimultaneously[6]. A detailed description of this technique will be done

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