Arm motion estimation based on distributed representations and neurodynamics
Project/Area Number |
24760213
|
Research Category |
Grant-in-Aid for Young Scientists (B)
|
Allocation Type | Multi-year Fund |
Research Field |
Intelligent mechanics/Mechanical systems
|
Research Institution | Teikyo University |
Principal Investigator |
YAMANE Ken 帝京大学, 理工学部, 助教 (30581235)
|
Project Period (FY) |
2012-04-01 – 2015-03-31
|
Project Status |
Completed (Fiscal Year 2014)
|
Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2014: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2013: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2012: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
|
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 / 動作推定 / リカレントニューラルネット / 人支援システム |
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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Report
(4 results)
Research Products
(5 results)