エピソード記憶想起時の非定常脳波の解析

• 具永 基

  東京電機大学大学院先端科学技術研究科情報メディア工学専攻

• 川澄 正史

  東京電機大学大学院先端科学技術研究科情報メディア工学専攻

書誌事項

タイトル別名

• Nonstationary EEG Analysis in Episodic Memory Retrieval

抄録

Signal analysis methods for EEG signal are applied in blind signal separation, artifact removal, and feature extraction. These methods are utilized in time-domain or frequency-domain. A fundamental problem in EEG signal is that signal from the scalp exhibits nonstationarity and is mixed spatiotemporally. In this study, we analyzed EEG signal using a combination method with ICA(Independent Component Analysis)and semiparametric approach. Theta is associated with creative inspiration, deep mediation, and attention. During the episodic memory retrieval, the combination method is used to analyze data of7channels, in which EEG data from6electrodes and one EMG data are recorded every5ms. Subjects are required to push a right-side button when they recognized a presented word-pair is the same one as they previously remembered. Three seconds length EEG data are recorded before and after button pressed, then the artifact (eye blinking)is removed by ICA. Our proposed combination method is more effective than parametric AR model in context of extracting theta activity(4Hz to8Hz)during the episodic memory retrieval.

収録刊行物

• ライフサポート

  ライフサポート 20 (3), 107-114, 2008

  ライフサポート学会

キーワード

• Nonstationarity, Independent Component Analysis, Semiparametric, Electroencephalogram,Episodic Memory Retrieval

詳細情報

• CRID: 1390001204365772928
• NII論文ID: 10029237634
• NII書誌ID: AA11947931
• DOI: 10.5136/lifesupport.20.107
• ISSN: 18845827
• ISSN: 13419455
• Web Site: https://search.jamas.or.jp/link/ui/2008348111
• 本文言語コード: ja
• データソース種別:
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  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可