Presentation 2014-03-18
An Extraction of Muscle Synergies in the Grasping Task by the Integration of Hand Shape Information and EMG Signal
Katsunari MASUZAKI, Naohiro FUKUMURA,
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Abstract(in English) Since a human has a large number of muscles, it is thought that controlling the enormous degrees of freedom is difficult. However, the human achieves the movement skillfully and it is not known how the central nervous system controls and coordinates many degrees of freedom. One of the major hypothesis to solve this problem is the mechanism of muscle synergies. In this study, we focused on the extraction of the muscle synergies in a grasping task. At first, we confirmed the feature extraction from EMG using principal component analysis. After that, we examined a neural network model for extracting the correlated information between different kinds of information. As a result, we confiremed that the neural network model could extract the muscle synergies in the grasping task from the hand shape and EMG signal.
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Keyword(in English) Electromyogram / Grasping / Muscle synergy / Neural network model / Auto-encoder
Paper # HIP2013-82
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Committee HIP
Conference Date 2014/3/10(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) An Extraction of Muscle Synergies in the Grasping Task by the Integration of Hand Shape Information and EMG Signal
Sub Title (in English)
Keyword(1) Electromyogram
Keyword(2) Grasping
Keyword(3) Muscle synergy
Keyword(4) Neural network model
Keyword(5) Auto-encoder
1st Author's Name Katsunari MASUZAKI
1st Author's Affiliation Toyohashi University of Technology()
2nd Author's Name Naohiro FUKUMURA
2nd Author's Affiliation Toyohashi University of Technology
Date 2014-03-18
Paper # HIP2013-82
Volume (vol) vol.113
Number (no) 501
Page pp.pp.-
#Pages 6
Date of Issue