Phonocardiography diagnosis can be improved by modern techniques of signal processing. It is shown that the wavelet transform provides enough features of the PCG signals that will help clinics to obtain qualitative and quantitative measurements of the time-frequency PCG signal characteristics and consequently aid to diagnosis. Abnormal heartbeat sounds may contain, in addition to the first and second sounds, Si and S2, murmurs and aberrations caused by different pathological conditions of the cardiovascular system. This work investigates the analysis of the heartbeat cardiac sounds (or the phonocardiogram signal) using the time-frequency analysis by using the continuous version of the wavelet transforms method. We show here a comparative study of normal and abnormal heart sounds (or phonocardiogram signals), whose scalograms exhibit noticeable morphological differences in terms of duration and spectral composition of sounds. These differences suggest that the cochlear-wavelet-based scalograms can become an interesting approach to design automatic diagnosis systems.