2014 Fiscal Year Final Research Report
Arm motion estimation based on distributed representations and neurodynamics
Project/Area Number |
24760213
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Intelligent mechanics/Mechanical systems
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Research Institution | Teikyo University |
Principal Investigator |
YAMANE Ken 帝京大学, 理工学部, 助教 (30581235)
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Project Period (FY) |
2012-04-01 – 2015-03-31
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Keywords | 軌道アトラクタ / 選択的不感化 / 分散表現 / 神経力学系 / 表面筋電位 / 運動推定 / 人支援 |
Outline of Final Research Achievements |
From this study, we propose a method of processing sequences of motions based only on distributed representations and neurodynamics. To assess the method’s applicability, we constructed a motion estimation system using a trajectory attractor model: a recurrent neural network with continuous-time dynamics. Experimentally obtained results from surface myoelectric signals from an arm show that the system estimated 15 complex hand motions with average accuracy of about 86%, demonstrating the great potential of this system.
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Free Research Field |
知的情報処理
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