書誌事項
- タイトル別名
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- J164024 Remarks on Control of Communication Robot's Manipulator using Surface Electromyogram
抄録
Many studies of human-machine interface systems based on electromyogram(EMG) for controlling robot manipulators and prosthetic hands have conducted worldwide. This paper investigates a gesture classification of an upper limb from surface EMG sensors are mounted on the user's upper limb and four motions of elbow, i.e. flexion, extension, pronation and supination, are considered. In gesture classification experiments, the averaged classification rates are 74%, 66% and 53% can be achieved by using the RBF network, neural network and liner multiple regression, respectively. The experimental result shows the feasibility of the RBF network for this task.
収録刊行物
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- 年次大会
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年次大会 2013 (0), _J164024-1-_J164024-3, 2013
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390001205841840256
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- NII論文ID
- 110009935470
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- ISSN
- 24242667
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- 本文言語コード
- ja
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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