Literature DB >> 25238621

Robotic guidance induces long-lasting changes in the movement pattern of a novel sport-specific motor task.

Jakob Kümmel1, Andreas Kramer2, Markus Gruber2.   

Abstract

Facilitating the learning or relearning of motor tasks is one of the main goals of coaches, teachers and therapists. One promising way to achieve this goal is guiding the learner through the correct movement trajectory with the help of a robotic device. The aim of this study was to investigate if haptic guidance can induce long-lasting changes in the movement pattern of a complex sport-specific motor task. For this purpose, 31 subjects were assigned to one of three groups: EA (early angle, n=10), LA (late angle, n=11) and CON (control, n=10). EA and LA successfully completed five training sessions, which consisted of 50 robot-guided golf swings and 10 free swings each, whereas CON had no training. The EA group was guided through the movement with the wrist being bent early during backswing, whereas in the LA group it was bent late. The participants of EA and LA were not told about this difference in the movement patterns. To assess if the robot-guided training was successful in shaping the movement pattern, the timing of the wrist bending during the backswing in free swings was measured before (PRE), one day after (POST), and 7 days after (FUP) the five training sessions. The ANOVA (time×group×angle) showed that during POST and FUP, the participants of the EA group bent their wrist significantly earlier during the backswing than the other groups. Post-hoc analyses revealed that this interaction effect was mainly due to the differences in the wrist angle progression during the first 5° of the backswing. The robot-guided training was successful in shaping the movement pattern, and these changes persisted even after 7 days without further practice. This might have implications for the learning of complex motor tasks in general, as haptic guidance might quickly provide the beginner with an internal model of the correct movement pattern without having to direct the learner's attention towards the key points of the correct movement pattern.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Endpoint-controlled robot; Golf swing; Haptic guidance; Motor learning

Mesh:

Year:  2014        PMID: 25238621     DOI: 10.1016/j.humov.2014.08.003

Source DB:  PubMed          Journal:  Hum Mov Sci        ISSN: 0167-9457            Impact factor:   2.161


  3 in total

1.  Human social motor solutions for human-machine interaction in dynamical task contexts.

Authors:  Patrick Nalepka; Maurice Lamb; Rachel W Kallen; Kevin Shockley; Anthony Chemero; Elliot Saltzman; Michael J Richardson
Journal:  Proc Natl Acad Sci U S A       Date:  2019-01-07       Impact factor: 11.205

2.  Upper Limb Rehabilitation Tools in Virtual Reality Based on Haptic and 3D Spatial Recognition Analysis: A Pilot Study.

Authors:  Eun Bin Kim; Songee Kim; Onseok Lee
Journal:  Sensors (Basel)       Date:  2021-04-15       Impact factor: 3.576

3.  Assisting Movement Training and Execution With Visual and Haptic Feedback.

Authors:  Marco Ewerton; David Rother; Jakob Weimar; Gerrit Kollegger; Josef Wiemeyer; Jan Peters; Guilherme Maeda
Journal:  Front Neurorobot       Date:  2018-05-29       Impact factor: 2.650

  3 in total

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