Method of identifying individuals using VEP signals and neural network

Palaniappan, R. (2004) Method of identifying individuals using VEP signals and neural network. IEE Proceedings - Science, Measurement and Technology, 151 (1). pp. 16-20. ISSN 13502344

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Official URL: http://dx.doi.org/10.1049/ip-smt:20040003

Abstract

A method of identifying individuals using visual-evoked-potential (VEP) signals and neural network (NN) is proposed. In the approach, a backpropagation (BP) NN is trained to identify individuals using 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 10-fold cross-validation scheme. This shows promise for the approach to be developed further as a biometric identification system.

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 22 Aug 2011 07:04
Last Modified: 22 Aug 2011 07:04
URI: http://shdl.mmu.edu.my/id/eprint/2509

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