Literature DB >> 15282262

Learning to control arm stiffness under static conditions.

Mohammad Darainy1, Nicole Malfait, Paul L Gribble, Farzad Towhidkhah, David J Ostry.   

Abstract

We used a robotic device to test the idea that impedance control involves a process of learning or adaptation that is acquired over time and permits the voluntary control of the pattern of stiffness at the hand. The tests were conducted in statics. Subjects were trained over the course of 3 successive days to resist the effects of one of three different kinds of mechanical loads: single axis loads acting in the lateral direction, single axis loads acting in the forward/backward direction, and isotropic loads that perturbed the limb in eight directions about a circle. We found that subjects in contact with single axis loads voluntarily modified their hand stiffness orientation such that changes to the direction of maximum stiffness mirrored the direction of applied load. In the case of isotropic loads, a uniform increase in endpoint stiffness was observed. Using a physiologically realistic model of two-joint arm movement, the experimentally determined pattern of impedance change could be replicated by assuming that coactivation of elbow and double joint muscles was independent of coactivation of muscles at the shoulder. Moreover, using this pattern of coactivation control we were able to replicate an asymmetric pattern of rotation of the stiffness ellipse that was observed empirically. These findings are consistent with the idea that arm stiffness is controlled through the use of at least two independent co-contraction commands.

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Year:  2004        PMID: 15282262     DOI: 10.1152/jn.00596.2004

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  33 in total

1.  Postural constraints on movement variability.

Authors:  Daniel R Lametti; David J Ostry
Journal:  J Neurophysiol       Date:  2010-06-16       Impact factor: 2.714

2.  Grip forces during fast point-to-point and continuous hand movements.

Authors:  Paolo Viviani; Francesco Lacquaniti
Journal:  Exp Brain Res       Date:  2015-07-31       Impact factor: 1.972

3.  Transfer and durability of acquired patterns of human arm stiffness.

Authors:  Mohammad Darainy; Nicole Malfait; Farzad Towhidkhah; David J Ostry
Journal:  Exp Brain Res       Date:  2005-11-19       Impact factor: 1.972

4.  Modeling the biomechanical constraints on the feedforward control of endpoint stiffness.

Authors:  Xiao Hu; Wendy M Murray; Eric J Perreault
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

5.  Interactions with compliant loads alter stretch reflex gains but not intermuscular coordination.

Authors:  Eric J Perreault; Kuifu Chen; Randy D Trumbower; Gwyn Lewis
Journal:  J Neurophysiol       Date:  2008-02-20       Impact factor: 2.714

6.  Effects of human arm impedance on dynamics learning and generalization.

Authors:  Mohammad Darainy; Andrew A G Mattar; David J Ostry
Journal:  J Neurophysiol       Date:  2009-04-08       Impact factor: 2.714

7.  The influence of visual perturbations on the neural control of limb stiffness.

Authors:  Jeremy Wong; Elizabeth T Wilson; Nicole Malfait; Paul L Gribble
Journal:  J Neurophysiol       Date:  2008-07-30       Impact factor: 2.714

8.  Experimental measure of arm stiffness during single reaching movements with a time-frequency analysis.

Authors:  Davide Piovesan; Alberto Pierobon; Paul DiZio; James R Lackner
Journal:  J Neurophysiol       Date:  2013-08-14       Impact factor: 2.714

9.  Muscle cocontraction following dynamics learning.

Authors:  Mohammad Darainy; David J Ostry
Journal:  Exp Brain Res       Date:  2008-06-27       Impact factor: 1.972

10.  Muscle short-range stiffness can be used to estimate the endpoint stiffness of the human arm.

Authors:  Xiao Hu; Wendy M Murray; Eric J Perreault
Journal:  J Neurophysiol       Date:  2011-02-02       Impact factor: 2.714

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