Feature extraction schemes for BCI systems

Brain-computer Interfaces (BCIs) are control and communication systems based on acquisition and processing of brain signals to control a computer or an external device. Usually, BCI is focused in recognizing acquired events by different neuroimage methods, but the most used is the electroencephalography (EEG). Feature extraction over EEG signals for BCI systems is crucial to the classification performance. In this paper a comparison between various methods for feature extraction of EEG signals in BCI systems is presented. Different methodologies were taken into account, both at extracting frequency information from each electrode as for extracting shared information between electrodes.