Literature DB >> 31374732

The effect of skill level matching in dyadic interaction on learning of a tracing task.

Simone Kager, Asif Hussain, Adele Cherpin, Alejandro Melendez-Calderon, Atsushi Takagi, Satoshi Endo, Etienne Burdet, Sandra Hirche, Marcelo H Ang, Domenico Campolo.   

Abstract

Dyadic interaction between humans has gained great research interest in the last years. The effects of factors that influence the interaction, as e.g. roles or skill level matching, are still not well understood. In this paper, we further investigated the effect of skill level matching between partners on learning of a visuo-motor task. Understanding the effect of skill level matching is crucial for applications in collaborative rehabilitation. Fifteen healthy participants were asked to trace a path while being subjected to a visuo-motor rotation (Novice). The Novices were paired with a partner, forming one of the three Dyad Types: a) haptic connection to another Novice, b) haptic connection to an Expert (no visuo-motor rotation), or c) no haptic. The intervention consisted of a Familiarization phase, followed by a Training phase, in which the Novices were learning the task in the respective Dyad Type, and a Test phase in which the learning was assessed (haptic connection removed, if any). Results suggest that learning of the task with a haptic connection to an Expert was least beneficial. However, during the Training phase the dyads comprising an Expert clearly outperformed the dyads with matched skill levels. The results point towards the same direction as previous findings in literature and can be explained by current motor-learning theories. Future work needs to corroborate these preliminary results.

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Year:  2019        PMID: 31374732     DOI: 10.1109/ICORR.2019.8779485

Source DB:  PubMed          Journal:  IEEE Int Conf Rehabil Robot        ISSN: 1945-7898


  3 in total

Review 1.  Human-machine-human interaction in motor control and rehabilitation: a review.

Authors:  Emek Barış Küçüktabak; Sangjoon J Kim; Yue Wen; Kevin Lynch; Jose L Pons
Journal:  J Neuroeng Rehabil       Date:  2021-12-27       Impact factor: 4.262

2.  Robotic Assisted Upper Limb Training Post Stroke: A Randomized Control Trial Using Combinatory Approach Toward Reducing Workforce Demands.

Authors:  Aamani Budhota; Karen S G Chua; Asif Hussain; Simone Kager; Adèle Cherpin; Sara Contu; Deshmukh Vishwanath; Christopher W K Kuah; Chwee Yin Ng; Lester H L Yam; Yong Joo Loh; Deshan Kumar Rajeswaran; Liming Xiang; Etienne Burdet; Domenico Campolo
Journal:  Front Neurol       Date:  2021-06-02       Impact factor: 4.003

3.  Haptic human-human interaction does not improve individual visuomotor adaptation.

Authors:  Niek Beckers; Edwin H F van Asseldonk; Herman van der Kooij
Journal:  Sci Rep       Date:  2020-11-16       Impact factor: 4.379

  3 in total

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