Parameters of Noise Suppression Based on Wavelet Transform for Phonocardiographic Signals

Abstract

While heart disease is one of the three major diseases, only well-qualified doctors can evaluate phonocardiographic signals. This calls for an easily available system that can automatically diagnose phonocardiographic signals. When recording in a room, suppression is required as these signals are heavily contaminated by noise from various sources such as air conditioners and fans. Wavelet transform is one method for denoising phonocardiographic signals, but appropriate parameters are required. In this study, we investigated both normal and abnormal phonocardiographic signals to determine the appropriate use of single and multilevel thresholds and the best types of wavelet functions. The experiment results show that the most appropriate wavelet function is Symlet14 and multilevel thresholding is best for low SNRs.