Presentation	2005/3/21 Anticipatory neural-feedback control of human quiet standing Satoshi TANIGUCHI, Taishin NOMURA,
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Abstract(in English)	We prepared a differential equation model of human upright balance in a computer. It includes Hill type muscle models and skeletal system. The subject was asked to maintain the model's balance using his electromyograms from soleus and tibialis anterior, which were fed into the muscle model as its neural commands in real-time. We show that, even when parameter values of the model were tuned so that the model's upright posture could not be established via stiffness control neither conventional feedback control with feedback transmission delay, the subject could learn a new control strategy how he could maintain the model's balance.
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Keyword(in English)	upright posture / stiffness control / feedback delay
Paper #	NC2004-148
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Conference Information
Committee	NC
Conference Date	2005/3/21(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)	Anticipatory neural-feedback control of human quiet standing
Sub Title (in English)
Keyword(1)	upright posture
Keyword(2)	stiffness control
Keyword(3)	feedback delay
1st Author's Name	Satoshi TANIGUCHI
1st Author's Affiliation	Dept. of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University()
2nd Author's Name	Taishin NOMURA
2nd Author's Affiliation	Dept. of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University
Date	2005/3/21
Paper #	NC2004-148
Volume (vol)	vol.104
Number (no)	758
Page	pp.pp.-
#Pages	6
Date of Issue