Key result
Coiflet wavelet filtering improves fetal phonocardiogram signal-to-noise ratio by ~7 dB.
Why the study?
Fetal phonocardiogram signals are heavily contaminated by noise, making filtering mandatory for clinical use.
Does a specific combination of Wavelet transform mother Wavelet and thresholding settings improve noise reduction and fetal heart rate estimation accuracy in fetal phonocardiography?
Does a specific combination of Wavelet transform mother Wavelet and thresholding settings improve noise reduction and fetal heart rate estimation accuracy in fetal phonocardiography?
Absolute Event Rate: 22.9% vs 15.6%
p-value: p=< 10^-37
Identifying an optimal Wavelet filtering algorithm improves the automatic processing of fetal phonocardiograms, which may facilitate continuous, low-cost fetal heart rate monitoring.
May improve fetal phonocardiogram processing for monitoring; leaves open prospective clinical validation.
Fetal heart rate (FHR) monitoring can serve as a benchmark to identify high-risk fetuses. Fetal phonocardiogram (FPCG) is the recording of the fetal heart sounds (FHS) by means of a small acoustic sensor placed on maternal abdomen. Being heavily contaminated by noise, FPCG processing implies mandatory filtering to make FPCG clinically usable. Aim of the present study was to perform a comparative analysis of filters based on Wavelet transform (WT) characterized by different combinations of mothers Wavelet and thresholding settings. By combining three mothers Wavelet (4th-order Coiflet, 4th-order Daubechies and 8th-order Symlet), two thresholding rules (Soft and Hard) and three thresholding algorithms (Universal, Rigorous and Minimax), 18 different WT-based filters were obtained and applied to 37 simulated and 119 experimental FPCG data (PhysioNet/PhysioBank). Filters performance was evaluated in terms of reliability in FHR estimation from filtered FPCG and noise reduction quantified by the signal-to-noise ratio (SNR). The filter obtained by combining the 4th-order Coiflet mother Wavelet with the Soft thresholding rule and the Universal thresholding algorithm was found to be optimal in both simulated and experimental FPCG data, since able to maintain FHR with respect to reference (138.7[137.7; 140.8] bpm vs. 140.2[139.7; 140.7] bpm, P > 0.05, in simulated FPCG data; 139.6[113.4; 144.2] bpm vs. 140.5[135.2; 146.3] bpm, P > 0.05, in experimental FPCG data) while strongly incrementing SNR (25.9[20.4; 31.3] dB vs. 0.7[-0.2; 2.9] dB, P < 10⁻¹⁴, in simulated FPCG data; 22.9[20.1; 25.7] dB vs. 15.6[13.8; 16.7] dB, P < 10⁻³⁷, in experimental FPCG data). In conclusion, the WT-based filter obtained combining the 4th-order Coiflet mother Wavelet with the thresholding settings constituted by the Soft rule and the Universal algorithm provides the optimal WT-based filter for FPCG filtering according to evaluation criteria based on both noise and clinical features.
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Tomassini et al. (2019) studied Fetal heart rate monitoring (n=156). 4th-order Coiflet Wavelet filter with Soft rule and Universal algorithm vs. Unfiltered / reference FPCG signal was evaluated on Signal-to-noise ratio (SNR) in experimental FPCG data (p=< 10^-37). The 4th-order Coiflet Wavelet filter with Soft rule and Universal algorithm increased the median signal-to-noise ratio in experimental fetal phonocardiograms to 22.9 dB vs 15.6 dB (p<10^-37).
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