A method of building binary classifiers for classification of brain electrical activity data into one or more neurological classes is described. The method comprises the steps of extracting quantitative features from the brain electrical activity data, and reducing the pool of extracted features into a computationally manageable and statistically relevant set of features which can then be used for designing one or more classifiers.
METHOD OF BUILDING CLASSIFIERS FOR REAL-TIME CLASSIFICATION OF NEUROLOGICAL STATES