Toward 'optimal' schemes of robot assistance to facilitate motor skill learning.
Identifieur interne : 000A43 ( Main/Merge ); précédent : 000A42; suivant : 000A44Toward 'optimal' schemes of robot assistance to facilitate motor skill learning.
Auteurs : Angelo Basteris [Italie] ; Vittorio SanguinetiSource :
- Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference [ 1557-170X ] ; 2011.
English descriptors
- KwdEn :
- MESH :
- methods : Computer-Assisted Instruction, Robotics.
- physiology : Learning, Motor Skills.
- Humans, Man-Machine Systems.
Abstract
We investigate whether and on what circumstances physical interaction with a robot may facilitate the acquisition of a novel motor skill. We focus on two different motor tasks: (i) intermanual transfer of cursive handwriting and (ii) acquisition of a putting skill. In the case of handwriting, we found that intermanual transfer is facilitated by forms of interaction that account for the temporal aspects of the movements. In the case of putting, we found that guidance is helpful in improving longitudinal error (a matter of speed accuracy), but not directional error (a matter of position accuracy). Based on these results, we draw some tentative conclusions on which tasks can benefit from guidance, and how robots should be programmed to maximize their effect.
DOI: 10.1109/IEMBS.2011.6090658
PubMed: 22254814
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pubmed:22254814Le document en format XML
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<author><name sortKey="Basteris, Angelo" sort="Basteris, Angelo" uniqKey="Basteris A" first="Angelo" last="Basteris">Angelo Basteris</name>
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<front><div type="abstract" xml:lang="en">We investigate whether and on what circumstances physical interaction with a robot may facilitate the acquisition of a novel motor skill. We focus on two different motor tasks: (i) intermanual transfer of cursive handwriting and (ii) acquisition of a putting skill. In the case of handwriting, we found that intermanual transfer is facilitated by forms of interaction that account for the temporal aspects of the movements. In the case of putting, we found that guidance is helpful in improving longitudinal error (a matter of speed accuracy), but not directional error (a matter of position accuracy). Based on these results, we draw some tentative conclusions on which tasks can benefit from guidance, and how robots should be programmed to maximize their effect.</div>
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