From principal to independent component analysis of brain signals

Author

Vigario, R.N.

Author_Institution

GMD-FIRST, Berlin

Volume

2

fYear

2001

fDate

2001

Firstpage

1970

Abstract

The purpose of this paper is to introduce the attendee/reader of the special session on component analysis and brain signals to, or refresh the concepts of the classical principal component analysis (PCA) and the more recent independent component analysis (ICA). Some motivations for their use in the context of electromagnetic brain signal processing are given. An illustrative example in event related studies is as well provided.

Keywords

bioelectric potentials; electroencephalography; magnetoencephalography; medical signal processing; principal component analysis; EEG; MEG; artifact removal; brain signals; electromagnetic brain signal processing; essential data structures; event related studies; independent component analysis; medical diagnostic techniques; multivariate data handling; Biological neural networks; Covariance matrix; Eigenvalues and eigenfunctions; Electroencephalography; Independent component analysis; Magnetic analysis; Magnetoencephalography; Principal component analysis; Signal analysis; Statistical distributions;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7211-5

Type

conf

DOI

10.1109/IEMBS.2001.1020615

Filename

1020615