Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system

Gido Hakvoort, B. Reuderink, Michel Obbink

    Research output: Book/ReportReportProfessional

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    Abstract

    Using steady-state visually evoked potential (SSVEP) in brain-computer interface (BCI) systems is the subject of a lot of research. One of the most popular and widely used detection method is using a power spectral density analysis (PSDA). Lately there have been some new methods emerging, one of them is using canonical correlation analysis (CCA) which seems to have some promising improvements and advantages compared to traditional SSVEP detection methods, like better signal-to-noise ratio (SNR), lower inter-subject variability and the possibility to use harmonic frequencies, i.e., a serie of frequencies which have the same fundamental frequency. In this research two different SSVEP detection methods, one using PSDA and one using CCA are compared. The results show that the CCA-based detection method performs significantly better than the PSDA-based detection method. The increase of performance can in particular be seen when using harmonic frequencies. While the PSDA-based detection method has difficulties detecting harmonic frequencies, the CCA-based detection method is able to detect harmonic frequencies.
    Original languageUndefined
    Place of PublicationEnschede
    PublisherCentre for Telematics and Information Technology (CTIT)
    Number of pages12
    Publication statusPublished - 21 Feb 2011

    Publication series

    NameCTIT Technical Report Series
    PublisherCentre for Telematics and Information Technology, University of Twente
    No.TR-CTIT-11-03
    ISSN (Print)1381-3625

    Keywords

    • steady-state visually evoked potentials
    • EWI-19680
    • EEG
    • Detection
    • Human computer interaction
    • IR-76127
    • Brain-Computer Interfaces
    • METIS-277558

    Cite this

    Hakvoort, G., Reuderink, B., & Obbink, M. (2011). Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. (CTIT Technical Report Series; No. TR-CTIT-11-03). Enschede: Centre for Telematics and Information Technology (CTIT).
    Hakvoort, Gido ; Reuderink, B. ; Obbink, Michel. / Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. Enschede : Centre for Telematics and Information Technology (CTIT), 2011. 12 p. (CTIT Technical Report Series; TR-CTIT-11-03).
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    abstract = "Using steady-state visually evoked potential (SSVEP) in brain-computer interface (BCI) systems is the subject of a lot of research. One of the most popular and widely used detection method is using a power spectral density analysis (PSDA). Lately there have been some new methods emerging, one of them is using canonical correlation analysis (CCA) which seems to have some promising improvements and advantages compared to traditional SSVEP detection methods, like better signal-to-noise ratio (SNR), lower inter-subject variability and the possibility to use harmonic frequencies, i.e., a serie of frequencies which have the same fundamental frequency. In this research two different SSVEP detection methods, one using PSDA and one using CCA are compared. The results show that the CCA-based detection method performs significantly better than the PSDA-based detection method. The increase of performance can in particular be seen when using harmonic frequencies. While the PSDA-based detection method has difficulties detecting harmonic frequencies, the CCA-based detection method is able to detect harmonic frequencies.",
    keywords = "steady-state visually evoked potentials, EWI-19680, EEG, Detection, Human computer interaction, IR-76127, Brain-Computer Interfaces, METIS-277558",
    author = "Gido Hakvoort and B. Reuderink and Michel Obbink",
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    Hakvoort, G, Reuderink, B & Obbink, M 2011, Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. CTIT Technical Report Series, no. TR-CTIT-11-03, Centre for Telematics and Information Technology (CTIT), Enschede.

    Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. / Hakvoort, Gido; Reuderink, B.; Obbink, Michel.

    Enschede : Centre for Telematics and Information Technology (CTIT), 2011. 12 p. (CTIT Technical Report Series; No. TR-CTIT-11-03).

    Research output: Book/ReportReportProfessional

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    T1 - Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system

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    AU - Reuderink, B.

    AU - Obbink, Michel

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    Y1 - 2011/2/21

    N2 - Using steady-state visually evoked potential (SSVEP) in brain-computer interface (BCI) systems is the subject of a lot of research. One of the most popular and widely used detection method is using a power spectral density analysis (PSDA). Lately there have been some new methods emerging, one of them is using canonical correlation analysis (CCA) which seems to have some promising improvements and advantages compared to traditional SSVEP detection methods, like better signal-to-noise ratio (SNR), lower inter-subject variability and the possibility to use harmonic frequencies, i.e., a serie of frequencies which have the same fundamental frequency. In this research two different SSVEP detection methods, one using PSDA and one using CCA are compared. The results show that the CCA-based detection method performs significantly better than the PSDA-based detection method. The increase of performance can in particular be seen when using harmonic frequencies. While the PSDA-based detection method has difficulties detecting harmonic frequencies, the CCA-based detection method is able to detect harmonic frequencies.

    AB - Using steady-state visually evoked potential (SSVEP) in brain-computer interface (BCI) systems is the subject of a lot of research. One of the most popular and widely used detection method is using a power spectral density analysis (PSDA). Lately there have been some new methods emerging, one of them is using canonical correlation analysis (CCA) which seems to have some promising improvements and advantages compared to traditional SSVEP detection methods, like better signal-to-noise ratio (SNR), lower inter-subject variability and the possibility to use harmonic frequencies, i.e., a serie of frequencies which have the same fundamental frequency. In this research two different SSVEP detection methods, one using PSDA and one using CCA are compared. The results show that the CCA-based detection method performs significantly better than the PSDA-based detection method. The increase of performance can in particular be seen when using harmonic frequencies. While the PSDA-based detection method has difficulties detecting harmonic frequencies, the CCA-based detection method is able to detect harmonic frequencies.

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    KW - Human computer interaction

    KW - IR-76127

    KW - Brain-Computer Interfaces

    KW - METIS-277558

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    Hakvoort G, Reuderink B, Obbink M. Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. Enschede: Centre for Telematics and Information Technology (CTIT), 2011. 12 p. (CTIT Technical Report Series; TR-CTIT-11-03).