Abstract
This paper is concerned a “The Wigner distribution (WD)” analysis of the Heart cardiac (or phonocardiogram signals: PCG). The Wigner distribution (WD) and the corresponding WVD (Wigner Ville Distribution) have shown good performances in the analysis of non-stationary and quantitative measurements of the time-frequency PCG signal characteristics. It is shown that these transforms provides enough features of the PCG signals that will help clinics to obtain diagnosis.
Highlights
Heartbeat sound analysis by auscultation is still insufficient to diagnose some heart diseases
The Wigner distribution (WD) and the corresponding WVD (Wigner Ville Distribution) have shown good performances in the analysis of nonstationary signals. This comes from the ability of the WD to separate signals in both time and frequency directions
One advantage of the WD over the STFT is that it does not suffer from the time-frequency trade-off problem
Summary
Heartbeat sound analysis by auscultation is still insufficient to diagnose some heart diseases. The characteristics of the PCG signal and other features such as heart sounds S1 and S2 location; the number of components for each sound; their frequency content; their time interval; all can be measured more accurately by digital signal processing techniques. The WD was applied to heart sound signal it shows no success in displaying or separating the signal components in both the time and frequency direction [6], it provides high time-and frequencyresolution in simple monocomponent signal analysis [8]
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