Literature DB >> 9628423

A comparison of curvatures of left and right hand movements in a simple pointing task.

J J Boessenkool1, E J Nijhof, C J Erkelens.   

Abstract

Human arm movements towards visual targets are remarkably reproducible in several tasks and conditions. Various authors have reported that trajectories of unconstrained point-to-point movements are slightly curved, smooth and have bell-shaped velocity profiles. The hand paths of such movements show small - but significant - curvatures throughout the workspace. The cause of these curvatures is still obscure. Traditionally this curvature is explained as the result of an optimisation process or is ascribed to mechanical or dynamic properties of the effector system. Recently, however, it has been suggested that these curvatures are due at least partly, to the visual misperception of straight lines. To evaluate the latter hypothesis, we compared unconstrained, self-paced point-to-point movements that subjects made with their right and left hand. We assume that the visual misperception may depend on the position in the workspace, subject, etc. but not on the hand used to make the movement. Therefore we argue that if curvature is caused by a visual misperception of straight lines, curvatures should be the same for movements made with the left and right hand. Our experiments cast strong doubt on the hypothesis that curvatures are the result of a visual distortion, because curvatures of the left hand trajectories, mirrored in the mid-sagittal plane, are found to be accurately described by trajectories of the right hand. Estimates of the effect of visual distortion on movement curvature show that, if present, this effect is very small compared with other sources that contribute to movement curvature. We found that curvatures depend strongly on the subject and on the direction and distance of the movement. Curvatures do not seem to be caused purely by the dynamic properties of the arm, since curvatures do not change significantly with increasing movement velocity. Therefore, we conclude that curvatures reflect an inherent property of the control of multi-joint arm movements.

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Mesh:

Year:  1998        PMID: 9628423     DOI: 10.1007/s002210050410

Source DB:  PubMed          Journal:  Exp Brain Res        ISSN: 0014-4819            Impact factor:   1.972


  7 in total

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Authors:  E J Lai; A J Hodgson; T E Milner
Journal:  Exp Brain Res       Date:  2003-08-29       Impact factor: 1.972

2.  Bias and sensitivity in the haptic perception of geometry.

Authors:  Denise Y P Henriques; John F Soechting
Journal:  Exp Brain Res       Date:  2003-03-08       Impact factor: 1.972

3.  The influence of visual motion on motor learning.

Authors:  Zachary Danziger; Ferdinando A Mussa-Ivaldi
Journal:  J Neurosci       Date:  2012-07-18       Impact factor: 6.167

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Authors:  Bastien Berret; Christian Darlot; Frédéric Jean; Thierry Pozzo; Charalambos Papaxanthis; Jean Paul Gauthier
Journal:  PLoS Comput Biol       Date:  2008-10-24       Impact factor: 4.475

5.  A neural tracking and motor control approach to improve rehabilitation of upper limb movements.

Authors:  Michela Goffredo; Ivan Bernabucci; Maurizio Schmid; Silvia Conforto
Journal:  J Neuroeng Rehabil       Date:  2008-02-05       Impact factor: 4.262

6.  A biologically inspired neural network controller for ballistic arm movements.

Authors:  Ivan Bernabucci; Silvia Conforto; Marco Capozza; Neri Accornero; Maurizio Schmid; Tommaso D'Alessio
Journal:  J Neuroeng Rehabil       Date:  2007-09-03       Impact factor: 4.262

7.  Influence of the type of training task on intermanual transfer effects in upper-limb prosthesis training: A randomized pre-posttest study.

Authors:  Sietske Romkema; Raoul M Bongers; Corry K van der Sluis
Journal:  PLoS One       Date:  2017-11-30       Impact factor: 3.240

  7 in total

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