Literature DB >> 22013237

The role of haptic feedback when manipulating nonrigid objects.

Frédéric Danion1, Jonathan S Diamond, J Randall Flanagan.   

Abstract

Humans can learn to manipulate objects with complex dynamics, including nonrigid objects with internal degrees of freedom. The first aim of this study was to assess the contribution of haptic feedback when learning to manipulate a nonrigid object. The second aim was to evaluate how learning without haptic feedback influences subsequent learning with haptic feedback and vice versa. The task involved moving a simulated mass-attached to a grasped handle via a simulated, damped spring-to a target as quickly as possible. In the haptic plus vision (HV) condition, appropriate forces were applied to the handle, which was attached to a robot. In the vision only (V) condition, these forces were turned off. Participants completed 80 trials in each condition, with one-half starting with the HV condition. Both groups exhibited significant learning, as measured by movement time, in both conditions. For the condition performed first, initial performance, learning rate, and final performance were better with haptic feedback. Prior experience in the HV condition led to faster learning and better final performance in the V condition. However, prior experience in the V condition led to slower learning and worse final performance in the HV condition. In the V condition, all participants tended to keep the mass close to the hand. In the HV condition, participants who started with the HV condition allowed the mass to move away from the hand, whereas participants who started with the V condition continued to keep the mass close to the hand. We conclude that haptic feedback as well as prior experience with haptic feedback enhance the ability to control nonrigid objects and that training without haptic feedback can lead to persisting detrimental effects when subsequently dealing with haptic feedback.

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Year:  2011        PMID: 22013237     DOI: 10.1152/jn.00738.2011

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


  14 in total

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Journal:  J Neurophysiol       Date:  2016-07-27       Impact factor: 2.714

2.  Predictability, force, and (anti)resonance in complex object control.

Authors:  Pauline Maurice; Neville Hogan; Dagmar Sternad
Journal:  J Neurophysiol       Date:  2018-04-18       Impact factor: 2.714

Review 3.  Predictability and Robustness in the Manipulation of Dynamically Complex Objects.

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Journal:  J Neurophysiol       Date:  2015-02-25       Impact factor: 2.714

5.  Rapid Visuomotor Corrective Responses during Transport of Hand-Held Objects Incorporate Novel Object Dynamics.

Authors:  Jonathan S Diamond; Joseph Y Nashed; Roland S Johansson; Daniel M Wolpert; J Randall Flanagan
Journal:  J Neurosci       Date:  2015-07-22       Impact factor: 6.167

6.  Motor memories of object dynamics are categorically organized.

Authors:  Daniel M Wolpert; J Randall Flanagan; Evan Cesanek; Zhaoran Zhang; James N Ingram
Journal:  Elife       Date:  2021-11-19       Impact factor: 8.713

7.  Inertial torque during reaching directly impacts grip-force adaptation to weightless objects.

Authors:  T Giard; F Crevecoeur; J McIntyre; J-L Thonnard; P Lefèvre
Journal:  Exp Brain Res       Date:  2015-08-12       Impact factor: 1.972

8.  Eye Tracking of Occluded Self-Moved Targets: Role of Haptic Feedback and Hand-Target Dynamics.

Authors:  Frederic Danion; James Mathew; J Randall Flanagan
Journal:  eNeuro       Date:  2017-07-03

9.  Multiple motor memories are learned to control different points on a tool.

Authors:  James B Heald; James N Ingram; J Randall Flanagan; Daniel M Wolpert
Journal:  Nat Hum Behav       Date:  2018-04-09

10.  Asymmetrical Relationship between Prediction and Control during Visuomotor Adaptation.

Authors:  James Mathew; Pierre-Michel Bernier; Frederic R Danion
Journal:  eNeuro       Date:  2018-12-14
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