The use of Evolutionary Algorithm-based methods in EEG based BCI systems

Adham Atyabi, Martin Luerssen, Sean Fitzgibbon, David Powers

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    4 Citations (Scopus)


    Electroencephalogram (EEG) based Brain Computer Interface (BCI) is a system that uses human brain-waves recorded from the scalp as a means for providing a new communication channel by which people with limited physical communication capability can effect control over devices such as moving a mouse and typing characters. Evolutionary approaches have the potential to improve the performance of such system through providing a better sub-set of electrodes or features, reducing the required training time of the classifiers, reducing the noise to signal ratio, and so on. This chapter provides a survey on some of the commonly used EA methods in EEG study.

    Original languageEnglish
    Title of host publicationSwarm Intelligence for Electric and Electronic Engineering
    PublisherIGI Global
    Number of pages19
    ISBN (Print)9781466626669
    Publication statusPublished - 2012


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