PCG-Decompositor: A New Method for Fetal Phonocardiogram Filtering Based on Wavelet Transform Multi-level Decomposition

Abstract

Fetal phonocardiography (FPCG) is a non-invasive acoustic recording of fetal heart sounds (fHS). The fHS auscultation plays an important diagnostic role in assessing fetal wellbeing. Typically, FPCG is a non-stationary signal corrupted by the presence of noise. Thus, high-amplitude noise makes detection of FPCG waveforms challenging. Thus, appropriate filtering procedures have to be applied in order to make FPCG clinically usable. In the recent years, Wavelet transformation (WT) filtering has been proposed. In particular, aim of this study is to propose a new method based on WT multi-level decomposition filtering: PCG-Decompositor. To this aim, PCG-Decompositor based on Coiflets mother Wavelet (4th order, 9 levels of decomposition) was applied to 119 real FPCG tracings, all available in Physionet. PCG-Decompositor is a dependent thresholding technique based on FPCG multi-level decomposition analysis. Performances of PCG-Decompositor are computed against soft-thresholding denoising technique (STDT) in terms of Root Mean Square Error (RMSE) and fetal heart rate (fHR). In terms of fHR, PCG-Decompositor and STDT are compared between themselves and also with the so-called annotations, given by the average fHR using a simultaneous cardiotocography analysis. Original signal to noise ratio (SNR) values ranged from 7.1 dB to 24.4 dB; after application of PCG-Decompositor, SNR increased significantly, ranging from 9.7 dB to 26.9 dB (P < 10−7). Moreover, PCG-Decompositor showed a lower dispersion than STDT (RMSE: 0.7 dB vs. 1.2 dB), introduced no FPCG signal delay and left fHR unaltered. Thus, PCG-Decompositor could be a suitable and robust technique to denoise FPCG signals.