Phonocardiogram signal analysis: techniques and performance comparison.
This paper presents the applications of the spectrogram, Wigner distribution and wavelet transform analysis methods to the phonocardiogram (PCG) signals. A comparison between these three methods has shown the resolution differences between them. It is found that the spectrogram short-time Fourier transform (STFT), cannot detect the four components of the first sound of the PCG signal. Also, the two components of the second sound are inaccurately detected. The Wigner distribution can provide time-frequency characteristics of the PCG signal, but with insufficient diagnostic information: the four components of the first sound, S1, are not accurately detected and the two components of the second sound, S2, seem to be one component. It is found that the wavelet transform is capable of detecting the two components, the aortic valve component A2 and pulmonary valve component P2, of the second sound S2 of a normal PCG signal. These components are not detectable using the spectrogram or the Wigner distribution. However, the standard Fourier transform can display these two components in frequency but not the time delay between them. Furthermore, the wavelet transform provides more features and characteristics of the PCG signals that will help physicians to obtain qualitative and quantitative measurements of the time-frequency characteristics.
Obaidat
M S
MS
Department of Electrical Engineering, City University of New York, City College, NY 10031.
D001021:Aortic Valve / Q000502:physiology; D005583:Fourier Analysis; D006344:Heart Septal Defects, Atrial / Q000503:physiopathology; D006347:Heart Sounds / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D010701:Phonocardiography; D011664:Pulmonary Valve / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors