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Method of identifying individuals using VEP signals and neural network

Palaniappan, Ramaswamy (2004) Method of identifying individuals using VEP signals and neural network. IEE Proceedings: Science, Measurement and Technology, 151 (1). pp. 16-20. ISSN 1350-2344. (doi:10.1049/ip-smt:20040003) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
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
DOI/Identification number: 10.1049/ip-smt:20040003
Additional information: Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - IEE Proc Sci Meas Technol [Field not mapped to EPrints] AD - Fac. of Info. Science and Technology, Multimedia University, Melaka 75450, Malaysia [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints]
Uncontrolled keywords: Backpropagation, Computational methods, Digital filters, Electrocardiography, Electroencephalography, Gamma rays, Iterative methods, Optical character recognition, Sensory perception, Biometrics, Unimodal identification systems, Visual evoked potential (VEP) systems, Neural networks
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 17:32 UTC
Last Modified: 05 Jun 2019 14:58 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70756 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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