Characteristic analysis of visual evoked potentials and posterior dominant rhythm by use of EEG model

Kazuhiko Goto, Takenao Sugi, Yoshitaka Matsuda, Satoru Goto, Hiroki Fukuda, Yoshinobu Goto, Takao Yamasaki, Shozo Tobimatsu

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

3 被引用数 (Scopus)

抄録

Visual evoked potentials (VEPs) are the electrical responses from the brain concerned with visual information processing. Amplitude of VEPs is smaller than that of background EEG activity, and the stimulus-locked averaging method is usually used for obtained the waveform. VEP response to each stimulus is not completely the same however it is varying with its amplitude and duration. Therefore, amplitude of averaged VEP waveform deteriorates due to their variability in raw data. Feature extraction of background EEG activity during visual stimulation is also a one of significant items in VEP analysis. In that case, separation of VEP component and background EEG component (mainly posterior dominant rhythm) is crucial. In the past, we proposed the method of estimating both amplitude of VEP and dominant rhythm by use of EEG model. This present study, the proposed method was applied to actual recorded VEP data and its effectiveness was evaluated. EEGs with visual stimulus were recorded from nine healthy young adults. Usefulness of the proposed method was investigated by comparing the conventional power spectrum averaging method. The proposed method will be applicable to show an accurate VEP analysis and characteristic analysis of background activity under visual stimulus.

本文言語英語
ホスト出版物のタイトルICCAS 2013 - 2013 13th International Conference on Control, Automation and Systems
ページ233-236
ページ数4
DOI
出版ステータス出版済み - 2013
イベント2013 13th International Conference on Control, Automation and Systems, ICCAS 2013 - Gwangju, 大韓民国
継続期間: 10 20 201310 23 2013

出版物シリーズ

名前International Conference on Control, Automation and Systems
ISSN(印刷版)1598-7833

その他

その他2013 13th International Conference on Control, Automation and Systems, ICCAS 2013
国/地域大韓民国
CityGwangju
Period10/20/1310/23/13

All Science Journal Classification (ASJC) codes

  • 人工知能
  • コンピュータ サイエンスの応用
  • 制御およびシステム工学
  • 電子工学および電気工学

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