Constrained Tunable-Q Wavelet Transform based Analysis of Cardiac Sound Signals☆

Abstract In this paper, we present a new method for analysis of cardiac sound signals containing murmurs using constrained tunable-Q wavelet transform (TQWT). The fundamental heart sounds (FHS) and murmurs are separately reconstructed by suitably constraining TQWT. The segmentation of reconstructed murmurs into heart beat cycles is achieved using cardiac sound characteristic wave-form (CSCW) of reconstructed FHS. The frequency domain based approximate entropy, spectral entropy, Lempel-Ziv complexity, and time domain Shannon entropy are computed for each segmented heart beat cycles for least squares support vector machine (LS-SVM) based classification. The experimental results are included to show the effectiveness of the proposed method.

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