Literature DB >> 19450621

A modular planar robotic manipulandum with end-point torque control.

Ian S Howard1, James N Ingram, Daniel M Wolpert.   

Abstract

Robotic manipulanda are extensively used in investigation of the motor control of human arm movements. They permit the application of translational forces to the arm based on its state and can be used to probe issues ranging from mechanisms of neural control to biomechanics. However, most current designs are optimized for studying either motor learning or stiffness. Even fewer include end-point torque control which is important for the simulation of objects and the study of tool use. Here we describe a modular, general purpose, two-dimensional planar manipulandum (vBOT) primarily optimized for dynamic learning paradigms. It employs a carbon fibre arm arranged as a parallelogram which is driven by motors via timing pulleys. The design minimizes the intrinsic dynamics of the manipulandum without active compensation. A novel variant of the design (WristBOT) can apply torques at the handle using an add-on cable drive mechanism. In a second variant (StiffBOT) a more rigid arm can be substituted and zero backlash belts can be used, making the StiffBOT more suitable for the study of stiffness. The three variants can be used with custom built display rigs, mounting, and air tables. We investigated the performance of the vBOT and its variants in terms of effective end-point mass, viscosity and stiffness. Finally we present an object manipulation task using the WristBOT. This demonstrates that subjects can perceive the orientation of the principal axis of an object based on haptic feedback arising from its rotational dynamics.

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Year:  2009        PMID: 19450621     DOI: 10.1016/j.jneumeth.2009.05.005

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  89 in total

1.  Context-dependent partitioning of motor learning in bimanual movements.

Authors:  Ian S Howard; James N Ingram; Daniel M Wolpert
Journal:  J Neurophysiol       Date:  2010-08-04       Impact factor: 2.714

2.  Generalization and transfer of contextual cues in motor learning.

Authors:  A M E Sarwary; D F Stegeman; L P J Selen; W P Medendorp
Journal:  J Neurophysiol       Date:  2015-07-08       Impact factor: 2.714

3.  The temporal evolution of feedback gains rapidly update to task demands.

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4.  Novel magnetomechanical MR compatible vibrational device for producing kinesthetic illusion during fMRI.

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Journal:  Med Phys       Date:  2013-11       Impact factor: 4.071

5.  Rapid Automatic Motor Encoding of Competing Reach Options.

Authors:  Jason P Gallivan; Brandie M Stewart; Lee A Baugh; Daniel M Wolpert; J Randall Flanagan
Journal:  Cell Rep       Date:  2017-02-14       Impact factor: 9.423

6.  Risk sensitivity in a motor task with speed-accuracy trade-off.

Authors:  Arne J Nagengast; Daniel A Braun; Daniel M Wolpert
Journal:  J Neurophysiol       Date:  2011-03-23       Impact factor: 2.714

7.  Statistics of natural movements are reflected in motor errors.

Authors:  Ian S Howard; James N Ingram; Konrad P Körding; Daniel M Wolpert
Journal:  J Neurophysiol       Date:  2009-07-15       Impact factor: 2.714

8.  Transfer of dynamic learning across postures.

Authors:  Alaa A Ahmed; Daniel M Wolpert
Journal:  J Neurophysiol       Date:  2009-08-26       Impact factor: 2.714

9.  Nash equilibria in multi-agent motor interactions.

Authors:  Daniel A Braun; Pedro A Ortega; Daniel M Wolpert
Journal:  PLoS Comput Biol       Date:  2009-08-14       Impact factor: 4.475

10.  Changes of mind in decision-making.

Authors:  Arbora Resulaj; Roozbeh Kiani; Daniel M Wolpert; Michael N Shadlen
Journal:  Nature       Date:  2009-08-19       Impact factor: 49.962

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