Fetal phonocardiography is a well-known auscultation technique for evaluation of fetal health. However, murmurs that are synchronous with the maternal heartbeat can often be heard while listening to fetal heart sounds. Maternal placental murmurs (MPM) could be used to detect maternal cardiovascular and placental abnormalities, but the recorded MPMs are often contaminated by ambient interference and noise.
Objective: The aim of this study was to compare noise reduction methods to reduce noise in the recorded MPMs.
Approach: 1) Bandpass filtering (BPF), 2) a multichannel noise reduction (MCh) using either Wiener filter (WF), Least-mean-square or Independent component analysis, 3) a combination of BPF with wavelet transient reduction (WTR) and 4) a combination of MCh and WTR. The methods were tested on signals recorded with two microphone units placed on the abdomen of pregnant women with an electrocardiogram (ECG) recorded simultaneously. The performance was evaluated using coherence and heart cycle duration error (HCDError) as compared with the ECG.
Results: The mean of the absolute HCDError was 32.7 ms for the BPF with all methods significantly lower (p<0.05) than BPF. The lowest errors were obtained for WTR-WF where the HCDError ranged 16.68-17.72 ms for seven different filter orders. All methods had significantly different coherence measure compared with BPF (p<0.05). The lowest coherence was reached with WTR-WF (filter order 640) where the mean value decreased from 0.50 for BPF to 0.03.
Significance: These results show how noise reduction techniques such as WF combined with wavelet denoising can greatly enhance the quality of MPM recordings. .
Keywords: Adaptive Filtering; Fetal Phonocardiography; Independent Component Analysis; Least Mean Square Filter; Wavelets; Wiener Filter.
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