Nonnegative matrix factorization common spatial pattern in brain machine interface

H. Tsubakida, T. Shiratori, Atsushi Ishiyama, Y. Ono

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

    1 Citation (Scopus)

    Abstract

    Fast and accurate discrimination of Electroencephalography (EEG) data is necessary for controlling brain machine interface. This paper introduces a novel method to discriminate 2-class motor imagery states (left and right hand) using nonnegative matrix factorization (NMF), common spatial pattern (CSP) and random forest. Conventionally CSP is used after extracting frequency band segment of EEG signal, which is called bandpass-filtered CSP (BPCSP). Especially filter bank CSP (FBCSP) has been extensively used to extract feature vectors from EEG data. However in these methods, the range of frequency band needed to be specified in advance and the performance depends on the selected frequency band. Our new method can decide the frequency band automatically by using NMF (NMFCSP). After the feature vectors were extracted from EEG data, random forests (RF) method was adopted as a classification algorithm. The mean accuracy rate of 2-class classifier using NMFCSP was 78.8±3.27%. This is higher than the accuracy rate of BPCSP (64.4±8.53%) and FBCSP (68.4±6.81%).

    Original languageEnglish
    Title of host publication3rd International Winter Conference on Brain-Computer Interface, BCI 2015
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Print)9781479974948
    DOIs
    Publication statusPublished - 2015 Mar 30
    Event2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 - Gangwon-Do, Korea, Republic of
    Duration: 2015 Jan 122015 Jan 14

    Other

    Other2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015
    CountryKorea, Republic of
    CityGangwon-Do
    Period15/1/1215/1/14

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    Keywords

    • common spatial pattern
    • EEG classification
    • motor imagery
    • nonnegative matrix factorization
    • random forest

    ASJC Scopus subject areas

    • Human-Computer Interaction
    • Cognitive Neuroscience
    • Sensory Systems

    Cite this

    Tsubakida, H., Shiratori, T., Ishiyama, A., & Ono, Y. (2015). Nonnegative matrix factorization common spatial pattern in brain machine interface. In 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 [7073021] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2015.7073021