A framework for evaluating ICA methods of artifact removal from multichannel EEG

Kevin A. Glass; Gwen A. Frishkoff; Robert M. Frank; Colin Davey; Joseph Dien; Allen D. Malony; Don M. Tucker

doi:10.1007/978-3-540-30110-3_130

A framework for evaluating ICA methods of artifact removal from multichannel EEG

Kevin A. Glass, Gwen A. Frishkoff, Robert M. Frank, Colin Davey, Joseph Dien, Allen D. Malony, Don M. Tucker

Research output: Chapter in Book/Report/Conference proceeding › Chapter

21 Scopus citations

Abstract

We present a method for evaluating ICA separation of artifacts from EEG (electroencephalographic) data. Two algorithms, Infomax and FastICA, were applied to "synthetic data," created by superimposing simulated blinks on a blink-free EEG. To examine sensitivity to different data characteristics, multiple datasets were constructed by varying properties of the simulated blinks. ICA was used to decompose the data, and each source was cross-correlated with a blink template. Different thresholds for correlation were used to assess stability of the algorithms. When a match between the blink-template and a component was obtained, the contribution of the source was subtracted from the EEG. Since the original data were known a priori to be blink-free, it was possible to compute the correlation between these "baseline" data and the results of different decompositions. By averaging the filtered data, time-locked to the simulated blinks, we illustrate effects of different outcomes for EEG waveform and topographic analysis.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Carlos G. Puntonet, Alberto Prieto
Publisher	Springer Verlag
Pages	1033-1040
Number of pages	8
ISBN (Electronic)	3540230564, 9783540230564
DOIs	https://doi.org/10.1007/978-3-540-30110-3_130
State	Published - 2004
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3195
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-540-30110-3_130

Cite this

Glass, K. A., Frishkoff, G. A., Frank, R. M., Davey, C., Dien, J., Malony, A. D., & Tucker, D. M. (2004). A framework for evaluating ICA methods of artifact removal from multichannel EEG. In C. G. Puntonet, & A. Prieto (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 1033-1040). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3195). Springer Verlag. https://doi.org/10.1007/978-3-540-30110-3_130

A framework for evaluating ICA methods of artifact removal from multichannel EEG. / Glass, Kevin A.; Frishkoff, Gwen A.; Frank, Robert M. et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Carlos G. Puntonet; Alberto Prieto. Springer Verlag, 2004. p. 1033-1040 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3195).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Glass, KA, Frishkoff, GA, Frank, RM, Davey, C, Dien, J, Malony, AD & Tucker, DM 2004, A framework for evaluating ICA methods of artifact removal from multichannel EEG. in CG Puntonet & A Prieto (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3195, Springer Verlag, pp. 1033-1040. https://doi.org/10.1007/978-3-540-30110-3_130

Glass KA, Frishkoff GA, Frank RM, Davey C, Dien J, Malony AD et al. A framework for evaluating ICA methods of artifact removal from multichannel EEG. In Puntonet CG, Prieto A, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2004. p. 1033-1040. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-30110-3_130

Glass, Kevin A. ; Frishkoff, Gwen A. ; Frank, Robert M. et al. / A framework for evaluating ICA methods of artifact removal from multichannel EEG. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Carlos G. Puntonet ; Alberto Prieto. Springer Verlag, 2004. pp. 1033-1040 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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A framework for evaluating ICA methods of artifact removal from multichannel EEG

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