Evaluation of multimodal feedback effects on the time-course of motor learning in multimodal VR platform for rowing training

Korman Maria, Alessandro Filippeschi, Emanuele Ruffaldi, Yifat Shorr, Daniel Gopher

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study focused on the benefits of feedback augmentation for multi-session training of a complex motor-cognitive skill of indoor rowing in virtual environment. Specifically, we compared the effectiveness of augmented information feedback provided per training trial either visually, haptically or visual-haptically to the non-augmented condition, where no on-line feedback on task performance was afforded during training sessions. Surprisingly, the non-augmented training group was in general as successful in the long-term learning of a rowing skill as the augmented groups and according to some measures even superior to them. Our results also highlight important differences in the course of learning and skill representation upon different feedback conditions provided during training and may provide useful insights to the optimization for both sport and rehabilitation training protocols in VR.

Original languageAmerican English
Title of host publication2015 International Conference on Virtual Rehabilitation, ICVR 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages158-159
Number of pages2
ISBN (Electronic)9781479989843
DOIs
StatePublished - 16 Dec 2015
Event11th Annual International Conference on Virtual Rehabilitation, ICVR 2015 - Valencia, Spain
Duration: 9 Jun 201512 Jun 2015

Publication series

NameInternational Conference on Virtual Rehabilitation, ICVR

Conference

Conference11th Annual International Conference on Virtual Rehabilitation, ICVR 2015
Country/TerritorySpain
CityValencia
Period9/06/1512/06/15

Keywords

  • VR
  • augmented feedback
  • haptic feedback
  • indoor rowing
  • long-term training
  • motor learning
  • skill acquisition
  • visual feedback

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Computer Networks and Communications

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