Bringing BCI into everyday life: Motor imagery in a pseudo realistic environment

Stephanie Brandl, Johannes Höhne, Klaus Robert Muller, Wojciech Samek

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

Bringing Brain-Computer Interfaces (BCIs) into everyday life is a challenge because an out-of-lab environment implies the presence of variables that are largely beyond control of the user and the software application. This can severely corrupt signal quality as well as reliability of BCI control. Current BCI technology may fail in this application scenario because of the large amounts of noise, nonstationarity and movement artifacts. In this paper, we systematically investigate the performance of motor imagery BCI in a pseudo realistic environment. In our study 16 participants were asked to perform motor imagery tasks while dealing with different types of distractions such as vibratory stimulations or listening tasks. Our experiments demonstrate that standard BCI procedures are not robust to theses additional sources of noise, implicating that methods which work well in a lab environment, may perform poorly in realistic application scenarios. We discuss several promising research directions to tackle this important problem.

Original languageEnglish
Title of host publication2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
PublisherIEEE Computer Society
Pages224-227
Number of pages4
ISBN (Electronic)9781467363891
DOIs
Publication statusPublished - 2015 Jul 1
Event7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, France
Duration: 2015 Apr 222015 Apr 24

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2015-July
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
Country/TerritoryFrance
CityMontpellier
Period15/4/2215/4/24

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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