PuSH - Publikationsserver des Helmholtz Zentrums München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Moser, J. ; Sippel, K. ; Schleger, F. ; Preissl, H.*

Automated detection of fetal brain signals with principal component analysis.

Conf. Proc. IEEE Eng. Med. Biol. Soc., 6549-6552 (2019)
DOI PMC
Detection of fetal brain signals in fetal magnetoencephalographic recordings is - due to the low signal to noise ratio - challenging for researchers in this field. Up to now, state of the art is a manual evaluation of the signal. To make the evaluation more reproducible and less time consuming, an approach using Principal Component Analysis is introduced. Locations of the channels of most importance for the first three principal components are taken into account and their possibility of resembling brain activity evaluated. Data with auditory stimulation are taken for this analysis and trigger averaged signals from the channels selected as brain activity (manually & automatically) compared. Comparisons are done with regard to their average baseline activity, activity during a window of interest and timing and amplitude of their highest auditory event-related peak. The number of evaluable data sets showed to be lower for the automated compared to manual approach but auditory event-related peaks did not differ significantly in amplitude or timing and in both cases there was a significant activity change following the tone event. The given results and the advantage of reproducibility make this method a valid alternative.
Impact Factor
Scopus SNIP
Scopus
Cited By
Altmetric
0.000
0.461
1
Tags
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern

Zusatzinfos bearbeiten
Eigene Tags bearbeiten
Privat
Eigene Anmerkung bearbeiten
Privat
Auf Publikationslisten für
Homepage nicht anzeigen
Als besondere Publikation
markieren
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Sprache englisch
Veröffentlichungsjahr 2019
HGF-Berichtsjahr 2019
ISSN (print) / ISBN 1557-170X
Zeitschrift Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Quellenangaben Band: , Heft: , Seiten: 6549-6552 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.2019.8857283
Scopus ID 85077847310
PubMed ID 31947342
Erfassungsdatum 2020-01-28
[➜Korrektur melden]