Presentation 2005/11/12
Multi-Fingered Myoelectric Hand to Generate Various Motions from Surface EMG Signals
Masafumi MURAKAMI, Satoru SUEMATSU, Hirokazu YOKOI,
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Abstract(in English) Research Myoelectric Hands of using the conventional Neural Network is a method which learns the relation between EMG patterns and finger movement, and is reproduced using a Neural Network. But it doesn't sufficiently for user, because of a user needs to perform innumerable movement in everyday life and EMG changes by the muscle wasting and gap of the electrode position etc. So, the system that realize movement which unlearning pattern is necessary. Therefore the system combines or unites the components of motion, the system generates various motions. In this paper, we examine the system that generate motions from surface electromyogram on forearm.
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Keyword(in English) Myoelectric Hands / Neural Network / Volterra Neuron
Paper # NC2005-77
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Committee NC
Conference Date 2005/11/12(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Multi-Fingered Myoelectric Hand to Generate Various Motions from Surface EMG Signals
Sub Title (in English)
Keyword(1) Myoelectric Hands
Keyword(2) Neural Network
Keyword(3) Volterra Neuron
1st Author's Name Masafumi MURAKAMI
1st Author's Affiliation Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology()
2nd Author's Name Satoru SUEMATSU
2nd Author's Affiliation Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology
3rd Author's Name Hirokazu YOKOI
3rd Author's Affiliation Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology
Date 2005/11/12
Paper # NC2005-77
Volume (vol) vol.105
Number (no) 419
Page pp.pp.-
#Pages 4
Date of Issue