Patent Document ID: 8862581
Application ID: 12990156

Base Claim:
1. A method for concentration detection, the method comprising the steps of: extracting temporal features from brain signals; classifying the extracted temporal features using a classifier to give a score x 1 ; extracting spectral-spatial features from brain signals; selecting spectral-spatial features containing discriminative information between concentration and non-concentration states from the set of extracted spectral-spatial features; classifying the selected spectral-spatial features using a classifier to give a score x 2 ; combining the scores x 1 and x 2 to give a single score; and determining whether the subject is in a concentration state based on the single score; wherein the step of extracting spectral-spatial features of brain signals further comprises the steps of: extracting respective brain signal components in discrete frequency windows using filter banks to obtain spectral features of brain signals; and applying a common spatial pattern (CSP) algorithm to each of the spectral features using a CSP array to obtain the spectral-spatial features of brain signals.

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Claim 6:
6. The method as claimed in claim 1 , wherein the step of combining the scores x 1 and x 2 to give a single score further comprises the steps of: normalizing the scores x 1 and x 2 according to an equation (x−m x )/s x whereby m x and s x are the mean and standard deviation of outputs from the classifiers using training samples to give x 1n and x 2n respectively; assigning weights w 1 and w 2 to normalized scores x 1n and x 2n respectively; and combining the scores x 1n and x 2n according to an equation x 1n *w 1 +X 2n *w 2 to give a single score.