Document Detail


Experimentally confirmed mathematical model for human control of a non-rigid object.
MedLine Citation:
PMID:  14602835     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Determining the principles used to plan and execute movements is a fundamental question in neuroscience research. When humans reach to a target with their hand, they exhibit stereotypical movements that closely follow an optimally smooth trajectory. Even when faced with various perceptual or mechanical perturbations, subjects readily adapt their motor output to preserve this stereotypical trajectory. When humans manipulate non-rigid objects, however, they must control the movements of the object as well as the hand. Such tasks impose a fundamentally different control problem than that of moving one's arm alone. Here, we developed a mathematical model for transporting a mass-on-a-spring to a target in an optimally smooth way. We demonstrate that the well-known "minimum-jerk" model for smooth reaching movements cannot accomplish this task. Our model extends the concept of smoothness to allow for the control of non-rigid objects. Although our model makes some predictions that are similar to minimum jerk, it predicts distinctly different optimal trajectories in several specific cases. In particular, when the relative speed of the movement becomes fast enough or when the object stiffness becomes small enough, the model predicts that subjects will transition from a uni-phasic hand motion to a bi-phasic hand motion. We directly tested these predictions in human subjects. Our subjects adopted trajectories that were well-predicted by our model, including all of the predicted transitions between uni- and bi-phasic hand motions. These findings suggest that smoothness of motion is a general principle of movement planning that extends beyond the control of hand trajectories.
Authors:
Jonathan B Dingwell; Christopher D Mah; Ferdinando A Mussa-Ivaldi
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S.     Date:  2003-11-05
Journal Detail:
Title:  Journal of neurophysiology     Volume:  91     ISSN:  0022-3077     ISO Abbreviation:  J. Neurophysiol.     Publication Date:  2004 Mar 
Date Detail:
Created Date:  2004-02-19     Completed Date:  2004-04-13     Revised Date:  2007-11-14    
Medline Journal Info:
Nlm Unique ID:  0375404     Medline TA:  J Neurophysiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1158-70     Citation Subset:  IM    
Affiliation:
Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, Texas 78712, USA. jdingwell@mail.utexas.edu
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Hand / innervation,  physiology*
Hand Strength / physiology*
Humans
Models, Neurological
Models, Statistical
Movement / physiology
Robotics
Touch / physiology*
Grant Support
ID/Acronym/Agency:
F32-HD-08620-01/HD/NICHD NIH HHS; NS-35673/NS/NINDS NIH HHS
Comments/Corrections
Comment In:
J Neurophysiol. 2004 Mar;91(3):1109-10   [PMID:  14973324 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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