Analysis of heart sounds using time-frequency visual representations

Abstract

Phonocardiogram (PCG) is a pre-eminent tool to visualise the normal and abnormal heart sounds which helps the physician in the early detection of cardiac murmurs. PCG is a non-stationary signal with the rapid changes in frequency within one cardiac cycle. Hence, the choice of proper segmentation technique is a crucial factor in determining the success or failure of expert systems in the automated analysis of PCG signals. The normal and abnormal PCG signals from the publicly available database were used in this study. Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) were implemented to visualise the various components in the PCG signals. When FFT was applied to the normal and abnormal PCG signals, the resultant spectrums for both the signals were not much distinguishable. S1 and S2 heart sounds had overlapping frequencies. Moreover, preserving the time and frequency resolution is imperative in analysing the abnormal signals. DWT was implemented and visualised using time-frequency indicators. The study concludes that the DWT is more preferred for analysing the non-stationary PCG signal and it would be a less expensive technique to visualise the heart sounds. Simultaneous recording of ECG and PCG signal will provide a better visualisation of cardiac murmurs.