Comparison of ICA Algorithms for the Isolation of Biological Artifacts in Magnetoencephalography

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 magneto-encephalographic (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.

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