Abstract
Nowadays, fetal monitoring standard relies mainly on the analysis of fetal heart rate. However, signals like fetal electrocadiogram (fECG) and fetal phonocardiogram (fPCG) can offer complementary diagnostic information derived from the waveform analysis. The limitations of using, in particular, fPCG are: the signal to noise ratio (SNR) is very low because the recorded signal is a mixture of acoustic components originating not only from the fetus heart but also from the mother (maternal heart sounds (MHS), maternal organ sounds (MOS)) and other sources (power line interference, reverbaration noise, sensor and background noise). Moreover, it is dependent on gestational age, fetal and maternal positions, the data acquisition location. From the noise components the MHS presents a high correlation in the frequency domain with the fetal heart sounds (FHS). Thus, separation of MHS from acoustic recordings is not straightforward. In addition the MHS is a narrowband non-stationary signal. Thus, in this paper is proposed a method for fPCG enhancement from the recorded acoustic mixture based on the Esemeble Empirical Mode Decomposition (EEMD). This approach allows to analyze heart sounds into Intrinsic Mode Functions (IMFs) and it is adaptive and data driven. The performance of the proposed method is evaluated on a database with simulated fPCG signals.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Miller, D.A., Miller, L.A.: Electronic fetal heart rate monitoring: applying principles of patient safety. American Journal of Obstetrics & Gynecology 206(4), 278–283 (2018). https://doi.org/10.1016/j.ajog.2011.08.016. http://dx.doi.org/10.1016/j.ajog.2011.08.016
Nagel, J.H.: Progresses in fetal monitoring by improved data acquisition. IEEE engineering in medicine and biology magazine: the quarterly magazine of the Engineering in Medicine & Biology Society 3, 9–13 (1984). https://doi.org/10.1109/memb.1984.5006080
Mittra, A.K., Choudhary, N.K., Zadgaonkar, A.S.: Development of an artificial womb for acoustical simulation of mother’s abdomen. International Journal of Biomedical Engineering and Technology 1(3), 315–328 (2008). https://doi.org/10.1504/ijbet.2008.016964. https://www.inderscienceonline.com/doi/abs/10.1504/IJBET.2008.016964
Chetlur Adithya, P., Sankar, R., Moreno, W.A., Hart, S.: Trends in fetal monitoring through phonocardiography: Challenges and future directions. Biomedical Signal Processing and Control 33, 289–305 (2017). https://doi.org/10.1016/j.bspc.2016.11.007
Jabloun, M., Ravier, P., Buttelli, O., Lédée, R., Harba, R., Nguyen, L.D.: A generating model of realistic synthetic heart sounds for performance assessment of phonocardiogram processing algorithms. Biomedical Signal Processing and Control 8(5), 455–465 (2013). https://doi.org/10.1016/j.bspc.2013.01.002
Kovács, F., Horváth, C., Török, M., Hosszú, G.: Fetal breathing transmission in phonoeardiographic monitoring telemedicine systems. In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, pp. 5226–5229 (2006). https://doi.org/10.1109/iembs.2006.260360
Mittra, A.K., Choudhari, N.K.: Time-frequency analysis of foetal heart sound signal for the prediction of prenatal anomalies. Journal of Medical Engineering and Technology 33(4), 296–302 (2009). https://doi.org/10.1080/03091900802454384
Balogh, Á.T., Kovács, F.: Application of phonocardiography on preterm infants with patent ductus arteriosus. Biomedical Signal Processing and Control 6(4), 337–345 (2011). https://doi.org/10.1016/j.bspc.2011.05.009
Chourasia, V.S., Tiwari, A.K., Gangopadhyay, R.: A novel approach for phonocardiographic signals processing to make possible fetal heart rate evaluations. Digital Signal Processing: A Review Journal 30, 165–183 (2014). https://doi.org/10.1016/j.dsp.2014.03.009
Soysa, W.N., Godaliyadda, R.I., Wijayakulasooriya, J.V., Ekanayake, M.P., Kandauda, I.C.: Extraction and analysis of fetal heart signals with abnormalities an Eigen-analysis based approach. In: 2013 IEEE 8th International Conference on Industrial and Information Systems, ICIIS 2013 - Conference Proceedings, pp. 294–299 (2013). https://doi.org/10.1109/iciinfs.2013.6731998
Cesarelli, M., Ruffo, M., Romano, M., Bifulco, P.: Simulation of foetal phonocardiographic recordings for testing of FHR extraction algorithms. Computer Methods and Programs in Biomedicine 107(3), 513–523 (2012). https://doi.org/10.1016/j.cmpb.2011.11.008
Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.K., Stanley, H.E.: PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23), e215–e220 (2000). https://doi.org/10.1161/01.cir.101.23.e215. URL http://circ.ahajournals.org/cgi/doi/10.1161/01.CIR.101.23.e215
Wu, Z., Huang, N.E.: E nsemble Empirical Mode Decomposition: A Noise-Assited Data Analysis Method. Advances in Adaptive Data Analysis 01(01), 1–41 (2009). https://doi.org/10.1142/s1793536909000047
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Taralunga, D.D., Mihaela Neagu (Ungureanu), G. (2019). An Ensemble Empirical Mode Decomposition Based Method for Fetal Phonocardiogram Enhancement. In: Lhotska, L., Sukupova, L., Lacković, I., Ibbott, G. (eds) World Congress on Medical Physics and Biomedical Engineering 2018. IFMBE Proceedings, vol 68/2. Springer, Singapore. https://doi.org/10.1007/978-981-10-9038-7_73
Download citation
DOI: https://doi.org/10.1007/978-981-10-9038-7_73
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-9037-0
Online ISBN: 978-981-10-9038-7
eBook Packages: EngineeringEngineering (R0)