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- Uno Haruo
- Department of Systems Design and Informatics, Kyushu Institute of Technology
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- Yamaguchi Tomonari
- Department of Systems Design and Informatics, Kyushu Institute of Technology
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- Irie Jun
- Department of Systems Design and Informatics, Kyushu Institute of Technology
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- Maeda Makoto
- Department of Systems Design and Informatics, Kyushu Institute of Technology
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- Inoue Katsuhiro
- Department of Systems Design and Informatics, Kyushu Institute of Technology
抄録
Electroencephalograph (EEG) recorded during left and right hand motor imagery can be used to move a cursor to a target on a computer screen (such systems are called a brain computer interface: BCI). A BCI has been studied for one of rehabilitation programs intensively. However, the spatial resolution of EEG is inferior to other acquisition methods. Focusing attention on new information of EEG is required. In this paper, we proposed the Pulse Complex Model (PCM) as a new pattern recognition model to extract features from EEG concerning with motor imagery. In applying to the model, the parameters were estimated by using a Genetic Algorithm (GA). Then a discrimination rule based on a Support Vector Machine (SVM) was constructed. From the results, the best preprocessing and the optimal order of the model were estimated. On the basis of these results, some types of discriminant analyses were conducted. According to the results, a relation of approximation errors to the feature of motor imagery was revealed.
収録刊行物
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- Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
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Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2011 (0), 250-255, 2011-05-05
システム制御情報学会ストカスティックシステムシンポジウム
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詳細情報 詳細情報について
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- CRID
- 1390564237987746688
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- NII論文ID
- 130007377403
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- ISSN
- 21884749
- 21884730
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可