10. The method as claimed in claim 1 , the method further comprises the step of using training data to generate parameters for classifying the extracted temporal features using a classifier, for extracting spectral-spatial features from brain signals, for selecting spectral-spatial features containing discriminative information between the concentration and non-concentration states from the set of extracted spectral-spatial features and for classifying the selected spectral-spatial features using a classifier.
10. The method as claimed in claim 1 , the method further comprises the step of using training data to generate parameters for classifying the extracted temporal features using a classifier, for extracting spectral-spatial features from brain signals, for selecting spectral-spatial features containing discriminative information between the concentration and non-concentration states from the set of extracted spectral-spatial features and for classifying the selected spectral-spatial features using a classifier. 11. The method as claimed in claim 10 , wherein said parameters comprise one or more of a group consisting of projection matrices of CSPs for the CSP algorithm, parameters for selecting spectral-spatial features based on mutual information and a model for the classifiers.