Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography
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...
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| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9288669/ |
| _version_ | 1818853497029787648 |
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| author | Radek Martinek Katerina Barnova Rene Jaros Radana Kahankova Tomasz Kupka Michal Jezewski Robert Czabanski Adam Matonia Janusz Jezewski Krzysztof Horoba |
| author_facet | Radek Martinek Katerina Barnova Rene Jaros Radana Kahankova Tomasz Kupka Michal Jezewski Robert Czabanski Adam Matonia Janusz Jezewski Krzysztof Horoba |
| author_sort | Radek Martinek |
| collection | DOAJ |
| description | 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 (|ΔT<sub>i</sub>| ), 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 $\text {F1} = 93.12$ %. 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 %, PV = 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 %. |
| first_indexed | 2024-12-19T07:37:45Z |
| format | Article |
| id | doaj.art-f1b9727455644119a52816a73dfc1f4b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T07:37:45Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f1b9727455644119a52816a73dfc1f4b2022-12-21T20:30:32ZengIEEEIEEE Access2169-35362020-01-01822194222196210.1109/ACCESS.2020.30434969288669Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal PhonocardiographyRadek Martinek0https://orcid.org/0000-0003-2054-143XKaterina Barnova1https://orcid.org/0000-0001-5594-8294Rene Jaros2https://orcid.org/0000-0003-3346-6467Radana Kahankova3https://orcid.org/0000-0003-1555-9889Tomasz Kupka4Michal Jezewski5https://orcid.org/0000-0002-6026-0264Robert Czabanski6https://orcid.org/0000-0003-4737-2138Adam Matonia7Janusz Jezewski8Krzysztof Horoba9Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, Ostrava, Czech RepublicDepartment of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, Ostrava, Czech RepublicDepartment of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, Ostrava, Czech RepublicDepartment of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, Ostrava, Czech RepublicŁkasiewicz Research Network, Institute of Medical Technology and Equipment, Wrocław, PolandDepartment of Cybernetics, Nanotechnology, and Data Processing, Silesian University of Technology, Gliwice, PolandDepartment of Cybernetics, Nanotechnology, and Data Processing, Silesian University of Technology, Gliwice, PolandŁkasiewicz Research Network, Institute of Medical Technology and Equipment, Wrocław, PolandŁkasiewicz Research Network, Institute of Medical Technology and Equipment, Wrocław, PolandŁkasiewicz Research Network, Institute of Medical Technology and Equipment, Wrocław, PolandFetal 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 (|ΔT<sub>i</sub>| ), 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 $\text {F1} = 93.12$ %. 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 %, PV = 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 %.https://ieeexplore.ieee.org/document/9288669/Fetal phonocardiography (fPCG)fetal heart rate (fHR)non-invasive fetal monitoringempirical mode decomposition (EMD)ensemble empirical mode decomposition (EEMD)adaptive wavelet transform (AWT) |
| spellingShingle | Radek Martinek Katerina Barnova Rene Jaros Radana Kahankova Tomasz Kupka Michal Jezewski Robert Czabanski Adam Matonia Janusz Jezewski Krzysztof Horoba Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography IEEE Access Fetal phonocardiography (fPCG) fetal heart rate (fHR) non-invasive fetal monitoring empirical mode decomposition (EMD) ensemble empirical mode decomposition (EEMD) adaptive wavelet transform (AWT) |
| title | Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography |
| title_full | Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography |
| title_fullStr | Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography |
| title_full_unstemmed | Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography |
| title_short | Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography |
| title_sort | passive fetal monitoring by advanced signal processing methods in fetal phonocardiography |
| topic | Fetal phonocardiography (fPCG) fetal heart rate (fHR) non-invasive fetal monitoring empirical mode decomposition (EMD) ensemble empirical mode decomposition (EEMD) adaptive wavelet transform (AWT) |
| url | https://ieeexplore.ieee.org/document/9288669/ |
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