Presentation | 2012-07-02 Sparsification of Time Windows for EEG Signal Classification During Motor Imagery Hiroshi HIGASHI, Toshihisa TANAKA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In an EEG based Brain computer interface (BCI), a time-windowed signal having a fixed finite duration is classified into a class associated with a BCI task. The time window should be designed taking into account the duration when a user performs a task and a brain activity occurs. In order to find the appropriate length of the window that works well for BCI, this paper proposes a method for using a sparse time window being sparse in time domain. This method finds the optimal sparsification for the time window by a criterion based on a common spatial pattern method that is an effective method for feature extraction. By experiments, we show that the proposed method improves classification accuracy of BCI. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Brain computer interface / electroencephalogram / time window |
Paper # | CAS2012-2,VLD2012-12,SIP2012-34,MSS2012-2 |
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Committee | MSS |
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Conference Date | 2012/6/25(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Mathematical Systems Science and its applications(MSS) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Sparsification of Time Windows for EEG Signal Classification During Motor Imagery |
Sub Title (in English) | |
Keyword(1) | Brain computer interface |
Keyword(2) | electroencephalogram |
Keyword(3) | time window |
1st Author's Name | Hiroshi HIGASHI |
1st Author's Affiliation | Tokyo University of Agriculture and Technology:RIKEN Brain Science Institute() |
2nd Author's Name | Toshihisa TANAKA |
2nd Author's Affiliation | Tokyo University of Agriculture and Technology:RIKEN Brain Science Institute |
Date | 2012-07-02 |
Paper # | CAS2012-2,VLD2012-12,SIP2012-34,MSS2012-2 |
Volume (vol) | vol.112 |
Number (no) | 116 |
Page | pp.pp.- |
#Pages | 6 |
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