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

    21 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
    Country/TerritoryKorea, 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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