Motor priming as a brain-computer interface

Tom Stewart, Kiyoshi Hoshino, Andrzej Cichocki, Tomasz M. Rutkowski

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

Abstract

This paper reports on a project to overcome a difficulty associated with motor imagery (MI) in a brain-computer interface (BCI), in which user training relies on discovering how to best carry out the MI given only open-ended instructions. To address this challenge we investigate the use of a motor priming (MP), a similar mental task but one linked to a tangible behavioural goal. To investigate the efficacy of this approach in creating the changes in brain activity necessary to drive a BCI, an experiment is carried out in which the user is required to prepare and execute predefined movements. Significant lateralisations of alpha activity are discussed and significant classification accuracies of movement preparation versus no preparation are also reported; indicating that this method is promising alternative to motor imagery in driving a BCI.

Original languageEnglish
Title of host publicationNeural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings
EditorsSeiichi Ozawa, Kazushi Ikeda, Derong Liu, Akira Hirose, Kenji Doya, Minho Lee
PublisherSpringer Verlag
Pages538-545
Number of pages8
ISBN (Print)9783319466712
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event23rd International Conference on Neural Information Processing, ICONIP 2016 - Kyoto, Japan
Duration: 16 Oct 201621 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9948 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Neural Information Processing, ICONIP 2016
Country/TerritoryJapan
CityKyoto
Period16/10/1621/10/16

Keywords

  • Brain-computer interface (BCI)
  • EEG
  • Motor priming
  • Neurophysiological information processing and classification

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