Time-frequency analysis of the first and the second heartbeat sounds

Abstract This paper present the analysis and comparisons of the spectrogram, Wigner distribution and wavelet transform techniques to the phonocardiogram signal (PCG). An analysis on the first (S1) and the second cardiac sounds (S2) of the normal phonocardiogram signal is considered here to be able to distinguish the various techniques in their aptitude to separate and present suitably the internal components of these sounds (S1 and S2). A comparison between these methods has shown the resolution differences between them. It is found that the spectrogram short-time Fourier transform (STFT), cannot perfectly detect the two internals components of the first sound (M1 and T1: mitral and tricuspid component respectively) and also the two internals components of the second sound S2 (A2 and P2: atrial and pulmonary component respectively). The Wigner distribution (WD) can provide time-frequency characteristics of the sounds S1 and S2, but with insufficient diagnostic information: the two components, M1 and T1 for the sound S1 and the components A2 and P2 for the sound S2 and P2 are not accurately detected and seem to be one component only. It is found that the wavelet transform (WT) is capable of detecting the two internals components for each sound S1 and S2. However, the standard Fourier transform can display these internals components in frequency but not the time delay between them. Furthermore, the wavelet transform provides more features and characteristics of the sounds that will hemp physicians to obtain qualitative and quantitative measurements of the time-frequency characteristics.

[1]  Richard Kronland-Martinet,et al.  Detection of abrupt changes in sound signals with the help of wavelet transforms , 1987 .

[2]  M.d. Luisada,et al.  The Sounds of the Normal Heart , 1972 .

[3]  L. Feigen,et al.  Physical characteristics of sound and hearing. , 1971, The American journal of cardiology.

[4]  L. Marton,et al.  Advances in Electronics and Electron Physics , 1958 .

[5]  D. Evelyne Thèse de doctorat d'Etat , 1988 .

[6]  Paul R. White,et al.  Analysis of the second heart sound for diagnosis of paediatric heart disease , 1998 .

[7]  Metin Akay,et al.  Time frequency and wavelets in biomedical signal processing , 1998 .

[8]  S. Debbal,et al.  THE FAST FOURIER TRANSFORM AND THE CONTINUOUS WAVELET TRANSFORM ANALYSIS OF THE PHONOCARDIOGRAM SIGNAL , 2004 .

[9]  Stéphane Mallat,et al.  Multifrequency channel decompositions of images and wavelet models , 1989, IEEE Trans. Acoust. Speech Signal Process..

[10]  S. Zhong,et al.  Signal characterization from multiscale edges , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[11]  Olivier Rioul,et al.  Fast algorithms for discrete and continuous wavelet transforms , 1992, IEEE Trans. Inf. Theory.

[12]  P S Reddy,et al.  Normal and abnormal heart sounds in cardiac diagnosis. Part I: Systolic sounds. , 1985, Current problems in cardiology.

[13]  A. Grossmann,et al.  Cycle-octave and related transforms in seismic signal analysis , 1984 .

[14]  S. M. Debbal,et al.  HEARTBEAT SOUND ANALYSIS WITH THE WAVELET TRANSFORM , 2004 .

[15]  A Leatham,et al.  Auscultation and phonocardiography: a personal view of the past 40 years. , 1987, British heart journal.

[16]  M. Obaidat,et al.  Phonocardiogram signal analysis: techniques and performance comparison. , 1993, Journal of medical engineering & technology.