Presentation | 2010/6/11 Discrimination of Hand Motion from Surface EMG Signals Using a Selective Desensitization Neural Network Hiroshi KAWATA, Atsuo SUEMITSU, Masahiko MORITA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Real-time discrimination of hand motion from surface EMG signals is useful for developing surface EMG prosthetic arms, input interface and so on. However, existing discrimination methods are not practical because of low accuracy, a few discriminable motions, and many sample data required for training. This paper proposes a new discrimination method using a selective desensitization neural network (SDNN), which is excellent in generalization ability. The result of an evaluation experiment indicates that the proposed method is highly effective in quick and accurate discrimination of the hand motion based on a small number of samples. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Selective Desensitization / Neural Network / Electromyogram / Discrimination of Hand Motion |
Paper # | NC2010-6,NLP2010-6 |
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Committee | NC |
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Conference Date | 2010/6/11(1days) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Discrimination of Hand Motion from Surface EMG Signals Using a Selective Desensitization Neural Network |
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Keyword(1) | Selective Desensitization |
Keyword(2) | Neural Network |
Keyword(3) | Electromyogram |
Keyword(4) | Discrimination of Hand Motion |
1st Author's Name | Hiroshi KAWATA |
1st Author's Affiliation | Graduate School of Systems and Information Engineering, University of Tsukuba() |
2nd Author's Name | Atsuo SUEMITSU |
2nd Author's Affiliation | School of Information Science, Japan Advanced Institute of Science and Technology |
3rd Author's Name | Masahiko MORITA |
3rd Author's Affiliation | Graduate School of Systems and Information Engineering, University of Tsukuba |
Date | 2010/6/11 |
Paper # | NC2010-6,NLP2010-6 |
Volume (vol) | vol.110 |
Number (no) | 83 |
Page | pp.pp.- |
#Pages | 8 |
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