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    On Signal P-300 Detection for BCI Applications Based on Wavelet Analysis and ICA Preprocessing

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    This paper describes an experiment on the detection of a P-300 rhythm from electroencephalographic signals for brain computer interfaces applications. The P300 evoked potential is obtained from visual stimuli followed by a motor response from the subject. The EEG signals are obtained with a 14 electrodes Emotiv EPOC headset. Preprocessing of the signals includes denoising and blind source separation using an Independent Component Analysis algorithm. The P300 rhythm is detected through a time-scale analysis based on the discrete wavelet transform (DWT). Comparison using the Short Time Fourier Transform (STFT), and Wigner-Ville Distribution (WVD) indicates that the DWT outperforms the others as an analyzing tool for P300 rhythm detection.

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    Description

    Title : On Signal P-300 Detection for BCI Applications Based on Wavelet Analysis and ICA Preprocessing
    Author(s) : Gerardo Rosas-Cholula, Juan Manuel Ramirez-Cortes, Vicente Alarcon-Aquino, Jorge Martinez-Carballido, Pilar Gomez-Gil
    Abstract : This paper describes an experiment on the detection of a P-300 rhythm from electroencephalographic signals for brain computer interfaces applications. The P300 evoked potential is obtained from visual stimuli followed by a motor response from the subject. The EEG signals are obtained with a 14 electrodes Emotiv EPOC headset. Preprocessing of the signals includes denoising and blind source separation using an Independent Component Analysis algorithm. The P300 rhythm is detected through a time-scale analysis based on the discrete wavelet transform (DWT). Comparison using the Short Time Fourier Transform (STFT), and Wigner-Ville Distribution (WVD) indicates that the DWT outperforms the others as an analyzing tool for P300 rhythm detection.
    Keywords : p300, bci, dwt, ica

    Subject : unspecified
    Area : Other
    Language : English
    Year : 2010

    Affiliations Universidad de las Americas Puebla
    Journal : 2010 IEEE Electronics Robotics and Automotive Mechanics Conferen
    Publisher : IEEE
    Pages : 360 - 365
    Url : http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5692363
    Isbn : 978-1-4244-8149-1
    Doi : 10.1109/CERMA.2010.48

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