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Access type: UnknownAuthor: search.filters.author.Dechwechprasit, Panisa

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    Time-frequency based coherence analysis of red and green flickering visual stimuli for EEG-controlled applications
    (2017-03-23)
    Tantisatirapong, Suchada
    ;
    Dechwechprasit, Panisa
    ;
    Senavongse, Wongwit
    ;
    Phothisonothai, Montri
    The stimulus flickering at specific frequencies, or as known as steady-state visually evoked potential (SSVEP), can be recorded on an occipital area of the brain. SSVEP is used to interpret the EEG signal to detect the desired goal of the experiment. In this paper, we aim to investigate SSVE signal by means of magnitude-squared coherence (MSC) analysis between the red and green visual stimuli. In the experimental paradigm, we considered two parameters that are chromatic color and flickering frequency where an epoch interval was 10 seconds. The obtained results showed the statistically significant frequency-domain response and its maximum MSC coefficient in the theta and alpha bands for green and red flickers, respectively.
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    Time-frequency analysis of red-green visual flickers based on steady-state visual evoked potential recording
    (2017-02-21)
    Dechwechprasit, Panisa
    ;
    Phothisonothai, Montri
    ;
    Tantisatirapong, Suchada
    The study of brain activity can be done by visual stimulus flickering at specific frequencies, Steady-State Visual Evoked Potential or as known as SSVEP. SSVEP is to stimulate the EEG signal to locate the desired goal of the experiment when a visual stimulus flickering with different constant frequencies and same duration. We aim to present a case study of electroencephalogram (EEG) signal by analyzing the frequency response of the red and green light. The stimulation is based on SSVEP by dividing the trial into two trials: single light and two lights. We considered three parameters that are light color, frequency and epoch interval. The optimal experimental results showed the classification accuracy rate of 74% and 75% for single and two color lights, respectively. The results can be considerably applied to the brain-computer interface (BCI) system.