Presentation 2000/5/4
Estimate of arm posture from EMG signals
Osamu Shimada, Kyosuke Nishiyama, Makoto Sato, Yasuharu Koike,
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Abstract(in English) EMG signals are expected an application to a human interface or medical engineering. An artificial neural network model can learn the correlation between EMG signals and joint angles, so that model can estimate arm posture. Because this method requires much time for learning, it is difficult to estimate arm posture in real-time. The arm posture can′t be estimated properly because the condition of the electrode changes when it is re-covered even if the model which has been learned is used. It is all the more when a subject is different because of the different use of muscles. In this report, we proposed the normalize method of EMG signals and how to choose a model by using the network of 5 layer which an input signal is restored to.
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Keyword(in English) ENG / neural network model / normalization / restoration / realtime
Paper # PRMU2000-2, MI2000-2
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Committee MI
Conference Date 2000/5/4(1days)
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Paper Information
Registration To Medical Imaging (MI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Estimate of arm posture from EMG signals
Sub Title (in English)
Keyword(1) ENG
Keyword(2) neural network model
Keyword(3) normalization
Keyword(4) restoration
Keyword(5) realtime
1st Author's Name Osamu Shimada
1st Author's Affiliation Tokyo Institute of Technology()
2nd Author's Name Kyosuke Nishiyama
2nd Author's Affiliation Tokyo Institute of Technology
3rd Author's Name Makoto Sato
3rd Author's Affiliation Tokyo Institute of Technology
4th Author's Name Yasuharu Koike
4th Author's Affiliation Tokyo Institute of Technology
Date 2000/5/4
Paper # PRMU2000-2, MI2000-2
Volume (vol) vol.100
Number (no) 45
Page pp.pp.-
#Pages 8
Date of Issue