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Method of identifying individuals using VEP signals and neural network

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1 Author(s)
Palaniappan, R. ; Fac. of Inf. Sci. & Technol., Multimedia Univ., Melaka, Malaysia

A method of identifying individuals using visual-evoked-potential (VEP) signals and a neural network (NN) is proposed. In the approach, a backpropagation (BP) NN is trained to identify individuals using the gamma-band (30-50 Hz) spectral power ratio of VEP signals extracted from 61 electrodes located on the scalp of the brain. The gamma-band spectral-power ratio is computed using a zero-phase Butterworth digital filter and Parseval's time-frequency equivalence theorem. NN classification gives an average of 99.06% across 400 test VEP patterns from 20 individuals using a 10-fold cross-validation scheme. This shows promise for the approach to be developed further as a biometric identification system.

Published in:

Science, Measurement and Technology, IEE Proceedings -  (Volume:151 ,  Issue: 1 )