Abstract
Congenital heart disease (CHD) is a leading cause of infant death. To diagnose CHD, recordings from abdominal fetal electrocardiograms (fECG) can be used as a non-invasive tool. However, it is challenging to extract the fetal signal from fECG recordings partly due to the lack of data combining fECG recordings with a ground truth for the fetal signal, which can be obtained by using a scalp electrode during delivery. In this study, we present a computational model of a pregnant female torso, in which we simulate fetal and maternal ventricular excitation during sinus rhythm to derive fECGs, so as to enable isolated measurement of the fetal and maternal signal contributions. To extract the fetal contribution from a combined signal, we apply an adaptive filtering algorithm to wavelet transformed signals. Further development of the model may enable improvements in the recording and processing capabilities for fECGs, the reliable estimation of fetal heart rates, and possibly interpretation of fetal signal morphologies that could improve the overall diagnostic significance of abdominal fECGs.
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Uv, J.J., Myklebust, L., Rudsari, H.K., Welle, H., Arevalo, H. (2022). 3D Simulations of Fetal and Maternal Ventricular Excitation for Investigating the Abdominal ECG. In: McCabe, K.J. (eds) Computational Physiology. Simula SpringerBriefs on Computing(), vol 12. Springer, Cham. https://doi.org/10.1007/978-3-031-05164-7_2
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DOI: https://doi.org/10.1007/978-3-031-05164-7_2
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Publisher Name: Springer, Cham
Print ISBN: 978-3-031-05163-0
Online ISBN: 978-3-031-05164-7
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