Saccade-related EEG signals by ICA algorithms

Arao Funase, Motoaki Mouri, Yagi Tohru, Andrzej Cichocki, Ichi Takumi

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

Abstract

Saccade-related electroencephalogram (EEG) signals have been the subject of application oriented research by our group toward developing a brain computer interface (BCI). Our goal is to develop novel BCI based on eye movements system employing EEG signals online. Most of the analysis of the saccade-related EEG data has been performed using ensemble averaging approaches. In signal processing method for BCI, raw EEG signals are analyzed. In ensemble averaging method which is major EEG analysis is not suitable for processing raw EEG signals. In order to process raw EEG data, we use independent component analysis. This paper presents extraction rate of saccaderelated EEG signals by four ICA algorithms and six window size. As results of extracting rate focused on ICA algorithm, The JADE and Fast ICA have good results. As you know, calculation time in Fast ICA is faster than calculation time in JADE. Therefore, in this case, Fast ICA is best in order to extract saccaderelated ICs. Next, we focus on extracting rate in each windows. The windows not including EEG signals after saccade and the windows which has small window size is good extracting rate.

Original languageEnglish
Title of host publication2008 International Symposium on Information Theory and its Applications, ISITA2008
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 International Symposium on Information Theory and its Applications, ISITA2008 - Auckland, New Zealand
Duration: 7 Dec 200810 Dec 2008

Publication series

Name2008 International Symposium on Information Theory and its Applications, ISITA2008

Conference

Conference2008 International Symposium on Information Theory and its Applications, ISITA2008
Country/TerritoryNew Zealand
CityAuckland
Period7/12/0810/12/08

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