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Fully automated subtraction of heart activity for fetal magnetoencephalography data∗.
Conf. Proc. IEEE Eng. Med. Biol. Soc., 5685-5689 (2019)
Fetal magnetoencephalography (fMEG) is a method to record human fetal brain signals in pregnant mothers. Nevertheless the amplitude of the fetal brain signal is very small and the fetal brain signal is overlaid by interfering signals mainly caused by maternal and fetal heart activity. Several methods are used to attenuate the interfering signals for the extraction of the fetal brain signal. However currently used methods are often affected by a reduction of the fetal brain signal or redistribution of the fetal brain signal. To overcome this limitation we developed a new fully automated procedure for removal of heart activity (FAUNA) based on Principal Component Analysis (PCA) and Ridge Regression. We compared the results with an orthogonal projection (OP) algorithm which is widely used in fetal research. The analysis was performed on simulated data sets containing spontaneous and averaged brain activity. The new analysis was able to extract fetal brain signals with an increased signal to noise ratio and without redistribution of activity across sensors compared to OP. The attenuation of interfering heart signals in fMEG data was significantly improved by FAUNA and supports fully automated evaluation of fetal brain signal.
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Publication type
Article: Journal article
Document type
Scientific Article
ISSN (print) / ISBN
1557-170X
Conference Title
41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019
Conference Date
23-27 July 2019
Conference Location
Berlin
Quellenangaben
Pages: 5685-5689
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Non-patent literature
Publications
Reviewing status
Peer reviewed