Insider and outsider person authentication with minimum number of brain wave signals by neural and homogeneous identity filtering

Tangkraingkij, Preecha; Lursinsap, Chidchanok; Sanguansintukul, Siripun; Desudchit, Tayard
May 2013
Neural Computing & Applications;May2013 Supplement, Vol. 22, p463
Academic Journal
This study discusses the uniqueness of brain wave signals (electroencephalography, EEG) in a singular individual to determine personal authentication. The brain is the most complex biological structure known to man and its wave signals are very difficult to mimic or steal, EEG signals can be measured from different locations, but too many signals can degrade recognition speed and accuracy. A practical technique combining independent component analysis for signal cleaning and a supervised neural network for authenticating signals was proposed. This new process called homogeneous identify filtering was introduced to identify persons in considered and outside groups. From 16 different EEG signal locations, four truly relevant locations of 1,000 data points ( F, C, P, O), 1,500 data points ( F, F, C, P), and 3,000 data points ( F, F, P, O) by SOBIRO algorithm were selected. This selection was used to identify 20 persons with high accuracy within the test group. The significant location for authentication is position P which is the parietal lobe of the brain.


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