Wavelet filtering of fetal phonocardiography: A comparative analysis

Selene Tomassini; Annachiara Strazza; Agnese Sbrollini; Ilaria Marcantoni; Micaela Morettini; Sandro Fioretti; Laura Burattini

doi:10.3934/mbe.2019302

Wavelet filtering of fetal phonocardiography: A comparative analysis

Math Biosci Eng. 2019 Jun 29;16(5):6034-6046. doi: 10.3934/mbe.2019302.

Authors

Selene Tomassini¹, Annachiara Strazza², Agnese Sbrollini¹, Ilaria Marcantoni¹, Micaela Morettini¹, Sandro Fioretti², Laura Burattini^{1

2}

Affiliations

¹ Cardiovascular Bioengineering Lab, Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
² Laboratorio di Bioingegneria, Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.

PMID: 31499751
DOI: 10.3934/mbe.2019302

Abstract

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 (4^th-order Coiflet, 4^th-order Daubechies and 8^th-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 4^th-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 4^th-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.

Keywords: fetal monitoring; fetal phonocardiography; mothers wavelet; thresholding settings; wavelet transform filtering.

Publication types

Comparative Study

MeSH terms

Acoustics
Algorithms
Cardiotocography / methods
Computer Simulation
Female
Heart Rate, Fetal
Heart Sounds
Humans
Phonocardiography / methods*
Pregnancy
Prenatal Diagnosis / methods*
Reproducibility of Results
Signal Processing, Computer-Assisted
Signal-To-Noise Ratio
Wavelet Analysis*