Independent Component Analysis of EEG and Source Position Estimation


The KIPS Transactions:PartB , Vol. 9, No. 1, pp. 35-46, Feb. 2002
10.3745/KIPSTB.2002.9.1.35,   PDF Download:

Abstract

The EEG is a time series of electrical potentials representing the sum of a very large number of neuronal dendrite potentials in the brain. The collective dynamic behavior of neural mass of different brain structures can be assessed from EEG with depth electrodes measurements at regular time intervals. In recent years, the theory of nonlinear dynamics has developed methods for quantitative analysis of brain function. In this paper, we considered it is reasonable or not for ICA apply to EEG analysis. Then we applied ICA to EEG for big toe movement and separated the independent components for 15 samples. The strength of each independent component can be represented on the topological map. We represented ICA can be applied for time and spatial analysis of EEG.


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Cite this article
[IEEE Style]
E. S. Kim, "Independent Component Analysis of EEG and Source Position Estimation," The KIPS Transactions:PartB , vol. 9, no. 1, pp. 35-46, 2002. DOI: 10.3745/KIPSTB.2002.9.1.35.

[ACM Style]
Eung Soo Kim. 2002. Independent Component Analysis of EEG and Source Position Estimation. The KIPS Transactions:PartB , 9, 1, (2002), 35-46. DOI: 10.3745/KIPSTB.2002.9.1.35.