Characterization and Classification of EEG Attention Based on Fuzzy Entropy

Attention recognition is an essential component in many biofeedback applications. Many biofeedback training need attention recognition algorithm to calculate concentration quantification. This paper propose an fuzzy entropy (FuzzyEn) to extract attention level feature from EEG. The developed method was compared with other methods used for the concentration level recognition. EEG data collected from twelve healthy subjects. Experimental results demonstrate that average identification rate of FuzzyEn feature extraction method reaches 81%. The result demonstrated an efficiency of the proposed approach.