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Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review

Overview of attention for article published in Psychonomic Bulletin & Review, November 2012
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Title
Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review
Published in
Psychonomic Bulletin & Review, November 2012
DOI 10.3758/s13423-012-0333-8
Pubmed ID
Authors

Roland Sigrist, Georg Rauter, Robert Riener, Peter Wolf

Abstract

It is generally accepted that augmented feedback, provided by a human expert or a technical display, effectively enhances motor learning. However, discussion of the way to most effectively provide augmented feedback has been controversial. Related studies have focused primarily on simple or artificial tasks enhanced by visual feedback. Recently, technical advances have made it possible also to investigate more complex, realistic motor tasks and to implement not only visual, but also auditory, haptic, or multimodal augmented feedback. The aim of this review is to address the potential of augmented unimodal and multimodal feedback in the framework of motor learning theories. The review addresses the reasons for the different impacts of feedback strategies within or between the visual, auditory, and haptic modalities and the challenges that need to be overcome to provide appropriate feedback in these modalities, either in isolation or in combination. Accordingly, the design criteria for successful visual, auditory, haptic, and multimodal feedback are elaborated.

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Mendeley readers

The data shown below were compiled from readership statistics for 1,432 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 <1%
United Kingdom 7 <1%
Switzerland 5 <1%
Japan 4 <1%
France 3 <1%
Portugal 2 <1%
Italy 2 <1%
Brazil 2 <1%
Turkey 1 <1%
Other 11 <1%
Unknown 1387 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 308 22%
Student > Master 260 18%
Researcher 137 10%
Student > Bachelor 136 9%
Student > Doctoral Student 79 6%
Other 220 15%
Unknown 292 20%
Readers by discipline Count As %
Engineering 324 23%
Computer Science 141 10%
Psychology 128 9%
Sports and Recreations 119 8%
Neuroscience 78 5%
Other 300 21%
Unknown 342 24%