Denoising of Fetal Phonocardiogram Signal by Wavelet Transformation

Abstract

Auscultation is still one of the most basic analytical tools used to determine the fetal heart’s functional state as well as the first fetal well-being measure. It is called fetal phonocardiography (fPCG) in its modern form. The technique of fPCG is passive and can be used to track long-term. Robust signal processing techniques are required to denoise the signals in order to improve the diagnostic capabilities of fPCG. A linear filter is used to eliminate distortion and interference from the fPCG signals through conventional denoising techniques. This paper searched for optimal configuration of the wavelet based denoising system. Based on the experimental results, can be conclude that the signal should be decomposed on six levels. From this it can be seen that the lowest MSE (mean square error) value is the use of coiflets three with SURE threshold algorithm with hard threshold parameters.

A Review of Recent Advances and Future Developments in Fetal Phonocardiography

“…However, most authors do not deal with the issue of optimization or do not mention it. For most publications, testing is performed randomly, using a number of methods and alternatives, from which the one that achieves the best results is subsequently selected (see [37], [48]).…”

“…Their performances were evaluated using the SNR parameter and also by the reliability in estimating fHR from the filtered fPCG signal. According to the authors, the best results (for both groups of tested data) were obtained by combining the Coif4 wavelet base with the Soft thresholding rule and the Universal thresholding algorithm, as it was able to maintain the fHR value with respect to the reference (Ref fHR = 138.7, SIM fHR = 139.6, SU fHR = 140.5), see TableIV.r Faradisa et al in[48] dealt with the filtering of the fPCG signal using a WT-based filter on the data from the SUFHSDB database. The authors tested different types of wavelet bases (Coif3, Sym5, and Db6), thresholding (Soft, Hard) and the type of thresholding algorithm (Universal, Minimax, SURE).…”