Received November 13, 2020, accepted December 5, 2020, date of publication December 9, 2020, date of current version December 22, 2020. Digital Object Identifier 10.1109/ACCESS.2020.3043496 Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography RADEK MARTINEK 1 , (Member, IEEE), KATERINA BARNOVA 1 , RENE JAROS 1 , RADANA KAHANKOVA 1 , TOMASZ KUPKA 2 , MICHAL JEZEWSKI 3 , ROBERT CZABANSKI 3 , ADAM MATONIA 2 , JANUSZ JEZEWSKI 2 , (Senior Member, IEEE), AND KRZYSZTOF HOROBA 2 1 Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic 2 Łukasiewicz Research Network, Institute of Medical Technology and Equipment, 54-066 Wrocław, Poland 3 Department of Cybernetics, Nanotechnology, and Data Processing, Silesian University of Technology, 44-100 Gliwice, Poland Corresponding author: Rene Jaros (rene.jaros@vsb.cz) This work was supported in part by the Ministry of Education of the Czech Republic under Project SP2020/156, and in part by the European Regional Development Fund in the Research Centre of Advanced Mechatronic Systems Project, within the Operational Programme Research, Development, and Education, under Project CZ.02.1.01/0.0/0.0/16 019/0000867. ABSTRACT Fetal phonocardiography (fPCG) is a non-invasive technique for detection of fetal heart sounds (fHSs), murmurs and vibrations. This acoustic recording is passive and provides an alternative low-cost method to ultrasonographic cardiotocography (CTG). Unfortunately, the fPCG signal is often disturbed by the wide range of artifacts that make it difficult to obtain significant diagnostic information from this signal. The study focuses on the filtering of an fPCG signal containing three types of noise (ambient noise, Gaussian noise, and movement artifacts of the mother and the fetus) having different amplitudes. Three advanced signal processing methods: empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and adaptive wavelet transform (AWT) were tested and compared. The evaluation of the extraction was performed by determining the accuracy of S1 sounds detection and by determining the fetal heart rate (fHR). The evaluation of the effectiveness of the method was performed using signal-to-noise ratio (SNR), mean error of heart interval measurement ( |T i |), and the statistical parameters of accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and harmonic mean between SE and PPV (F1). Using the EMD method, ACC > 95% was achieved in 7 out of 12 types and levels of interference with average values of ACC = 88.73%, SE = 91.57%, PPV = 94.80% and F1 = 93.12%. Using the EEMD method, ACC > 95% was achieved in 9 out of 12 types and levels of interference with average values of ACC = 97.49%, SE = 97.89%, PPV = 99.53% and F1 = 98.69%. In this study, the best results were achieved using the AWT method, which provided ACC > 95% in all 12 types and levels of interference with average values of ACC = 99.34%, SE = 99.49%, PPV = 99.85% a F1 = 99.67%. INDEX TERMS Fetal phonocardiography (fPCG), fetal heart rate (fHR), non-invasive fetal monitoring, empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), adaptive wavelet transform (AWT). I. INTRODUCTION Electronic fetal monitoring is an important part of obstetrics, used mainly to prevent fetal hypoxia. Hypoxia is a dan- gerous condition, and if it is diagnosed, it is necessary to The associate editor coordinating the review of this manuscript and approving it for publication was Chuan Li. terminate the pregnancy by caesarean section [1]. In clin- ical practice, a cardiotocography (CTG) method, is used for fetal monitoring. However, fetal monitoring using CTG is burdened with a high degree of disagreement among obstetricians, leading to a high number of unnecessarily performed caesarean sections [2]–[5]. The efforts of sci- entists are focused on improving alternative methods for 221942 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 8, 2020