EEG Alpha Activity Detection by Fuzzy Reasoning

E. Huupponen, M. Lehtokangas, J. Saarinen, A. Värri, A. Saastamoinen, S-L. Himanen, J. Hasan

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

    1 Citation (Scopus)


    Automated systems are needed to assist the tedious visual analysis of polygraphic recordings. Most systems need detection of different electroencephalogram (EEG) waveforms. The problem in automated detection of alpha activity is the large inter-individual variability of its amplitude and duration. In this work, a fuzzy reasoning based method for the detection of alpha activity was designed and tested. The ranges of the fuzzy rules were determined based on feature statistics. The advantage of the presented detector is that no alpha amplitude threshold needs to be selected. The performance of the alpha detector with four modifications was assessed with ROC curves. When the true positive rate was 85%, the false positive rate was 13%, which is sufficient for sleep EEG analysis.

    Original languageEnglish
    Title of host publicationProceedings of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, July 25-28, 2001, Vancouver, British Columbia, Canada
    Number of pages6
    Publication statusPublished - 2001
    Publication typeA4 Article in conference proceedings
    EventJoint 9th IFSA World Congress and 20th NAFIPS International Conference - Vancouver, BC, Canada
    Duration: 25 Jul 200128 Jul 2001


    ConferenceJoint 9th IFSA World Congress and 20th NAFIPS International Conference
    CityVancouver, BC


    • Automatic detection
    • EEG alpha
    • Fuzzy reasoning

    Publication forum classification

    • Publication forum level 0

    ASJC Scopus subject areas

    • Computer Science(all)
    • Mathematics(all)


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