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Sippel, K. ; Moser, J. ; Schleger, F. ; Escalona-Vargas, D.* ; Preissl, H. ; Rosenstiel, W.* ; Spüler, M.*

Fully automated subtraction of heart activity for fetal magnetoencephalography data∗.

Conf. Proc. IEEE Eng. Med. Biol. Soc., 5685-5689 (2019)
DOI
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Sprache
Veröffentlichungsjahr 2019
HGF-Berichtsjahr 2019
ISSN (print) / ISBN 1557-170X
Konferenztitel 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019
Konferzenzdatum 23-27 July 2019
Konferenzort Berlin
Zeitschrift Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Quellenangaben Band: , Heft: , Seiten: 5685-5689 Artikelnummer: , Supplement: ,
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Diabetes Research and Metabolic Diseases (IDM)
POF Topic(s) 90000 - German Center for Diabetes Research
Forschungsfeld(er) Helmholtz Diabetes Center
PSP-Element(e) G-502400-001
DOI 10.1109/EMBC.2019.8856603
Scopus ID 85077845410
Erfassungsdatum 2020-01-28
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