Toward exoskeleton control based on steady state visual evoked potentials

No Sang Kwak, Klaus Robert Müller, Seong Whan Lee

Research output: Contribution to conferencePaperpeer-review

12 Citations (Scopus)

Abstract

Brain-machine interfaces (BMIs) are systems that establish a direct connection between the human brain and a machine. These systems are applicable to neuro-rehabilitation. In this study, we propose a method of finding optimal threshold of canonical correlation analysis (CCA) based steady state visual evoked potentials (SSVEPs) classification for detecting resting state and reducing misclassification. As a result, we successfully found optimal threshold for the best performance. This result shows the possibility of SSVEP based exoskeleton online control with a proposed method.

Original languageEnglish
DOIs
Publication statusPublished - 2014
Event2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 - Gangwon, Korea, Republic of
Duration: 2014 Feb 172014 Feb 19

Other

Other2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
CountryKorea, Republic of
CityGangwon
Period14/2/1714/2/19

Keywords

  • Brain Machine Interfaces
  • Electroencephalogram
  • Exoskeleton
  • Steady State Visual Evoked Potential (SSVEP)

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Human Factors and Ergonomics

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