Abstract
An experiment on the detection of a P-300 rhythm for potential applications on brain computer interfaces (BCI) using an Adaptive Neuro Fuzzy algorithm (ANFIS) is presented. P300 evoked potential is an electroencephalographic (EEG) signal obtained at the central-parietal region of the brain in response to rare or unexpected events. 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 using the discrete wavelet transform (DWT) applied on the preprocessed signal as a feature extractor, and further entered to the ANFIS system. Experimental results are presented.
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Ramirez-Cortes, J.M., Alarcon-Aquino, V., Rosas-Cholula, G., Gomez-Gil, P., Escamilla-Ambrosio, J. (2011). Anfis-Based P300 Rhythm Detection Using Wavelet Feature Extraction on Blind Source Separated Eeg Signals. In: Ao, SI., Amouzegar, M., Rieger, B. (eds) Intelligent Automation and Systems Engineering. Lecture Notes in Electrical Engineering, vol 103. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0373-9_27
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DOI: https://doi.org/10.1007/978-1-4614-0373-9_27
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