NDLI: Movement imagery classification on the basis of single-trial EEGs

Content Provider	IEEE Xplore Digital Library
Author	Hideyuki Maki, Hiroshi Takayanagi, Toshimasa Yamazaki, Ken-ichi Kamijo, Takahiro Yamanoi,
Copyright Year	2007
Description	Author affiliation: Dept. Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka 820-8502, Japan (Toshimasa Yamazaki,) \|\| Japan Technical Software Co., Ltd, Tokyo 108-0075, Japan (Hideyuki Maki,) \|\| Faculty of Engineering, Hokkai-Gakuen Univ., Sapporo 064-0926, Japan (Takahiro Yamanoi,) \|\| Information Science Research Center Co., Ltd, Tokyo 108-0014, Japan (Hiroshi Takayanagi,) \|\| NEC Nano Electronics Res. Labs, Tsukuba 305-0841, Japan (Ken-ichi Kamijo,)
Abstract	In order to develop a new brain-computer interface (BCI) using EEGs, the independent component analysis (ICA), multiple equivalent current dipole source localization (ECDL) method and then Hayashi’s quantification method II were applied to single-trial EEGs during movement imagery. Up to the 20th independent component, each of them contained one or two positive (or negative) peaks in terms of 32-channel EEGs reconstructed on the electrode surface by the deflation procedure, and these peaks were analyzed by 1- or 2-dipole source localization method. Moreover, the quantification method based on these ECDL results yielded a good discrimination between right- and left-hand movement imageries, even if regardless of the time course of the localization results, instead of only for one male subject.
Starting Page	3979
Ending Page	3983
File Size	306386
Page Count	5
File Format	PDF
ISBN	9781424409907
DOI	10.1109/ICSMC.2007.4414247
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Independent component analysis Magnetic analysis Image reconstruction Electrodes Rhythm Information science Grasping Magnetic resonance imaging Enterprise resource planning
Content Type	Text
Resource Type	Article

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