Selection of mother wavelet and denoising algorithm for analysis of foetal phonocardiographic signals

Abstract

This paper is aimed at the selection of suitable mother wavelet and denoising algorithm for the analysis of foetal phonocardiographic (fPCG) signals. Fourier based analysing tools have some limitations concerning frequency and time resolutions. Although wavelet transform (WT) overcomes these limitations, it requires proper selection of a mother wavelet and denoising algorithm. In this study a suitable mother wavelet is selected on the basis of properties of different wavelet families and characteristics of the fPCG signals. The universal threshold, minimax threshold and rigorous SURE threshold algorithms along with soft or hard thresholding rule have been compared to denoise these signals. The mean squared error (MSE) is used to evaluate the performance of these algorithms. The results show that the fourth order Coiflets wavelet has a better performance for the analysis of fPCG signals when using the rigorous SURE threshold denoising algorithm with soft thresholding rule. The proposed approach is simple and proves to be effective when applied to the selection of suitable mother wavelet and denoising algorithm for the fPCG signals. These denoised signals can be used for the accurate determination of foetal heart rate (FHR) and further diagnostic applications of the foetus.