Zugriffsnummer 19297
Dokumenttyp Konferenzartikel
Sprache Englisch
Titel Comparison of ICA algorithms for the isolation of biological artifacts in magnetoencephalography
Autor(in); Institution
Zavala-Fern.aacute.ndez, Heriberto; TU Berlin, Institut für Elektronik, Berlin, GERMANY
Sander-Thömmes, Tilmann; 8.2, Biosignale, PTB-Berlin
Burghoff, Martin; 8.2, Biosignale, PTB-Berlin
Orglmeister, Reinhold; TU Berlin, Institut für Elektronik, Berlin, GERMANY
Trahms, Lutz; 8.2, Biosignale, PTB-Berlin
Quelle/Jahr Independent component analysis and blind signal separation:(2006), 511 - 518
Schriftenreihe Lecture notes in computer science: 3889
Herausgeber(in)
Rosca, Justinian
ISBN 3-540-32630-8
DOI
Verlag Berlin [u.a.]: Springer
Konferenzangaben 6th International Conference, ICA 2006, Charleston, SC, 05-08, March, 2006, USA
Freie Schlagworte Magnetoencephalography ; Independent Component Analysis ; Artifact Suppression
Zusammenfassung The application of Independent Component Analysis (ICA) to achieve blind source separation is now an accepted technique in the field of biosignal processing. The reduction of biological artifacts in magneto- and electroencephalographic recordings is a frequent goal. Four of the most common ICA methods, extended Infomax, FastICA, JADE, and SOBI are compared here with respect to their ability to isolate magnetoencephalographic (MEG) artifacts. The four algorithms are applied to the same data set containing heart beat and eye movement artifacts. For a quantification of the result simple spatial and temporal correlation measures are suggested and the usage of reference signals. Of the four algorithms only JADE was marginally less successful.

Zitierung

Zavala-Fern.aacute.ndez, H., Sander-Thömmes, T., Burghoff, M., Orglmeister, R., & Trahms, L. (2006). Comparison of ICA algorithms for the isolation of biological artifacts in magnetoencephalography. 6th International Conference, ICA 2006, Charleston, SC, 05-08, March, 2006, USA. https://doi.org/10.1007/11679363_64

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