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Common spatial pattern (CSP) is a popular method for 2-class motor imagery electroencephalogram (EEG) classification. Filter bank common spatial pattern (FBCSP) is an improved version of CSP by introducing multiple frequency filters and a stage of feature selection. In FBCSP, methods for the feature selection stage can be various, and there is no criteria to guide the selection. To make the selection of a specific feature selection method reasonable, this paper tries to obey a guideline that the feature selection method should match with the classification method. Based on the proposed criteria above, this paper employs fisher linear discriminant (FLD) for classification and a corresponding Relief method for features selection.

An Implementation of FBCSP Replacing Feature Selection Method According to the Classifier