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We studied the performance of a double-spatial filtering method for classification of single-trial electroencephalography (EEG) data that couples the spherical surface Laplacian (SL) and independent component analysis (ICA). This method was evaluated in the context of a binary classification experiment with brain states driven by mental imagery of auditory and visual stimuli. A statistically significant...
In this paper we used Independent Component Analysis (ICA) model of EEG signals for preprocessing and then Discrete Wavelet Transform (DWT) analysis for feature extraction from EEG signal which this features are useful in BCI application. Then we used Fuzzy C-means (FCM) algorithm for recognition of some diseases like epileptic seizure, Cerebral Palsy (CP), etc. This project can be divided in three...
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