Presentation	2004/11/20 Myoelectric Hands control system using the correlation of each finger joint angle Hitoshi TESHIMA, Satoru SUEMATSU, Hirokazu YOKOI,
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Abstract(in English)	The conventional Myoelectric Hands using the neural network cannot reproduces the learned movement accurately. Because neural network has a low learning ability. Then the purpose of this study is the development of Myoelectric Hands to estimate accurately the condition of finger in each time. This study proposes Myoelectric Hands control system using the correlation of each finger joint angle and confirms the effectiveness.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	Myoelectric Hands / Neural Network / Correlation of each finger joint angle
Paper #	NC2004-105
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Conference Information
Committee	NC
Conference Date	2004/11/20(1days)
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Paper Information
Registration To	Neurocomputing (NC)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Myoelectric Hands control system using the correlation of each finger joint angle
Sub Title (in English)
Keyword(1)	Myoelectric Hands
Keyword(2)	Neural Network
Keyword(3)	Correlation of each finger joint angle
1st Author's Name	Hitoshi TESHIMA
1st Author's Affiliation	Kyushu Institute of Technology Graduate School of life Science and Systems Engineering()
2nd Author's Name	Satoru SUEMATSU
2nd Author's Affiliation	Kyushu Institute of Technology Graduate School of life Science and Systems Engineering
3rd Author's Name	Hirokazu YOKOI
3rd Author's Affiliation	Kyushu Institute of Technology Graduate School of life Science and Systems Engineering
Date	2004/11/20
Paper #	NC2004-105
Volume (vol)	vol.104
Number (no)	474
Page	pp.pp.-
#Pages	4
Date of Issue