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Investigating motor adaptation to stable and unstable tasks using haptic interfaces, EMG and fMRI
Our talk describes our general project, i.e. how we investigate the adaptation to stable and unstable tasks using EMG, fMRI and haptic interfaces. This short paper focuses on a spin-off. It describes a simple computational model of force and impedance in human arm movements, which can be used to sim...
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creator | Tee, K.P. Burdet, E. Chew, C.M. Milner, T.E. |
description | Our talk describes our general project, i.e. how we investigate the adaptation to stable and unstable tasks using EMG, fMRI and haptic interfaces. This short paper focuses on a spin-off. It describes a simple computational model of force and impedance in human arm movements, which can be used to simulate human motion and to improve the control of human-machine interfaces. This model, based on recent physiological findings, assumes that a) the central nervous system learns the force and impedance to perform the task successfully in a given stable or unstable dynamic environment; b) for stable interaction, stiffness is linearly related to the magnitude of the joint torque. Comparison with existing data shows that this simple model is able to predict impedance geometry well. |
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This short paper focuses on a spin-off. It describes a simple computational model of force and impedance in human arm movements, which can be used to simulate human motion and to improve the control of human-machine interfaces. This model, based on recent physiological findings, assumes that a) the central nervous system learns the force and impedance to perform the task successfully in a given stable or unstable dynamic environment; b) for stable interaction, stiffness is linearly related to the magnitude of the joint torque. 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Comparison with existing data shows that this simple model is able to predict impedance geometry well.</description><subject>Central nervous system</subject><subject>Computational modeling</subject><subject>Computer interfaces</subject><subject>Electromyography</subject><subject>Force control</subject><subject>Haptic interfaces</subject><subject>Humans</subject><subject>Impedance</subject><subject>Man machine systems</subject><subject>Motion control</subject><isbn>0780383524</isbn><isbn>9780780383524</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2003</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj9FKAzEURAMiqLVf4Es-wIUkN9lkH6XUutAiiD6Xu9mbGm2zZZMK_r2r9mmY4czAXLAbYZ0AB0bpKzbP-UMIIZu6kaCvGbbpi3KJOywx7fhhKMPIscdjmYIh8TLwXLDbE8fU81M6m4L5M_NT_u28T3D0PKZCY0BP-Z4vN6s_Pmxe2lt2GXCfaX7WGXt7XL4unqr186pdPKyrKK0pFaC3rumVFHUgK5W22PlghSFjg-8bJ7VE4Z234DT54GrlqRagO2eomw7O2N3_biSi7XGMBxy_txIUaDDwA8qgTgY</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Tee, K.P.</creator><creator>Burdet, E.</creator><creator>Chew, C.M.</creator><creator>Milner, T.E.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2003</creationdate><title>Investigating motor adaptation to stable and unstable tasks using haptic interfaces, EMG and fMRI</title><author>Tee, K.P. ; Burdet, E. ; Chew, C.M. ; Milner, T.E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-3ac789d2106fe71247abcf705e57fcd98141a0c8c7384ecf862ce6034b85eb803</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Central nervous system</topic><topic>Computational modeling</topic><topic>Computer interfaces</topic><topic>Electromyography</topic><topic>Force control</topic><topic>Haptic interfaces</topic><topic>Humans</topic><topic>Impedance</topic><topic>Man machine systems</topic><topic>Motion control</topic><toplevel>online_resources</toplevel><creatorcontrib>Tee, K.P.</creatorcontrib><creatorcontrib>Burdet, E.</creatorcontrib><creatorcontrib>Chew, C.M.</creatorcontrib><creatorcontrib>Milner, T.E.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEL</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tee, K.P.</au><au>Burdet, E.</au><au>Chew, C.M.</au><au>Milner, T.E.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Investigating motor adaptation to stable and unstable tasks using haptic interfaces, EMG and fMRI</atitle><btitle>SICE 2003 Annual Conference (IEEE Cat. No.03TH8734)</btitle><stitle>SICE</stitle><date>2003</date><risdate>2003</risdate><volume>1</volume><spage>591</spage><epage>595 Vol.1</epage><pages>591-595 Vol.1</pages><isbn>0780383524</isbn><isbn>9780780383524</isbn><abstract>Our talk describes our general project, i.e. how we investigate the adaptation to stable and unstable tasks using EMG, fMRI and haptic interfaces. This short paper focuses on a spin-off. It describes a simple computational model of force and impedance in human arm movements, which can be used to simulate human motion and to improve the control of human-machine interfaces. This model, based on recent physiological findings, assumes that a) the central nervous system learns the force and impedance to perform the task successfully in a given stable or unstable dynamic environment; b) for stable interaction, stiffness is linearly related to the magnitude of the joint torque. Comparison with existing data shows that this simple model is able to predict impedance geometry well.</abstract><pub>IEEE</pub></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Central nervous system Computational modeling Computer interfaces Electromyography Force control Haptic interfaces Humans Impedance Man machine systems Motion control |
title | Investigating motor adaptation to stable and unstable tasks using haptic interfaces, EMG and fMRI |
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