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Jorge Del Río Vera BCI competition 2003 Distinction of a left or right hand keypress Algorithm The algorithm used is based in a MLP neural network and a key feature extraction based in PCA (principal component analysis). The principal component analysis is computed for each channel, then the second principal mode is used (I have not used the first because it contains the normal activity of the brain instead the features to discriminate between left or rigth hand). This mode is correlated with the signals (only the signals of the left side of the brain are used, beacuse the information of the laterallity is contained in the second principal mode) and the delay of the maximun is used for training the net (a 12 component vector). The net used is a MLP with two inner layers in order to accelerate the convergence (10 and 5 neurons respectively) and the output layer has two neurons. Results Results are given in a matlab data file, it have the same order than the test signals and the class is given by a 0 or a 1. Detection of a left or right hand keypress