Electroencephalogram Based Biometric System: A Review

Abstract

EEG signals can be preferred as a biometric trait because of their uniqueness, robustness to spoof attacks, and many other advantages as compared to other commonly used identifiers such as finger print, palm print, and face recognition. A complete overview of biometric systems based on EEG signals, their acquisition, pre-processing, feature extraction, and classification at different frequency bands is presented in this paper. Comparison is made between various techniques and their efficiencies used in EEG-based biometric systems. Different signal acquisition methods (resting state, visual stimuli, cognitive activities) used in previous works have been discussed with their pros and cons. Nowaday’s researchers focus on low-cost EEG acquisition systems with a smaller number of electrodes with better accuracy. Databases used in this area are also discussed, some of them are public and some authors acquire their personal data. A table is provided which compares the results of different signal acquisition methods, pre-processing techniques, feature extraction, and classification techniques.