Feature extraction of EEG during motor imagery and cognition by using morphological MRA

Electroencephalograph (EEG) recordings during right and left hand motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. Recently, we have proposed the detection method of Error Potential in order to add the fail safe function to BCI system. In this paper, feature extraction method based on morphological multi-resolution analysis is introduced to extract features concerned with motor imagery and cognition simultaneously from EEG signals. Morphological filter is composed of nonlinear operation between signal and structural function. We propose some design methods of structural function that decide the filter characteristic of morphology. These algorithms are compared to DWT from the view point of filter characteristics. Consequently, effectiveness of our method is confirmed.