Research on relationship between saccade-related EEG signals and selection of electrode position by independent component analysis

Arao Funase, Motoaki Mouri, Andrzej Cichocki, Ichi Takumi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Our goal is to develop a novel BCI based on an eye movements system employing EEG signals on-line. Most of the analysis on EEG signals has been performed using ensemble averaging approaches. However, in signal processing methods for BCI, raw EEG signals are analyzed. In order to process raw EEG signals, we used independent component analysis(ICA). Previous paper presented extraction rate of saccade-related EEG signals by five ICA algorithms and eight window size. However, three ICA algorithms, the FastICA, the NG-FICA and the JADE algorithms, are based on 4th order statistic and AMUSE algorithm has an improved algorithm named the SOBI. Therefore, we must re-select ICA algorithms. In this paper, Firstly, we add new algorithms; the SOBI and the MILCA. Using the Fast ICA, the JADE, the AMUSE, the SOBI, and the MILCA. The SOBI is an improved algorithm based on the AMUSE and uses at least two covariance matrices at different time steps. The MILCA use the independency based on mutual information. We extract saccade-related EEG signals and check extracting rates. Secondly, we check relationship between window sizes of EEG signals to be analyzed and extracting rates. Thirdly, we researched on relationship between Saccade-related EEG signals and selection of electrode position by ICA. In order to develop the BCI, it is important to use a few electrode. In previous studies, we analyzed EEG signals using by 19 electrodes. In this study, we checked various combination of electrode.

Original languageEnglish
Title of host publicationNeural Information Processing
Subtitle of host publicationModels and Applications - 17th International Conference, ICONIP 2010, Proceedings
Pages74-81
Number of pages8
EditionPART 2
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event17th International Conference on Neural Information Processing, ICONIP 2010 - Sydney, NSW, Australia
Duration: 22 Nov 201025 Nov 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6444 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Neural Information Processing, ICONIP 2010
Country/TerritoryAustralia
CitySydney, NSW
Period22/11/1025/11/10

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