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Simplified fuzzy ARTMAP classification of individuals using optimal VEP channels

Ravi, K.V.R., Palaniappan, Ramaswamy, Heng, S.-H. (2006) Simplified fuzzy ARTMAP classification of individuals using optimal VEP channels. International Journal of Knowledge-Based and Intelligent Engineering Systems, 10 (6). pp. 445-452. ISSN 1327-2314. (doi:10.3233/KES-2006-10604) (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/10.3233/KES-2006-10604

Abstract

In previous studies, identification of individuals using 61 channel Visual Evoked Potential (VEP) signals from the brain has been shown to be feasible. These studies used neural network classification of gamma band spectral power of VEP signals from 20 individuals. This paper explores our continuing work in this area to include more subjects in the experiment and to reduce the number of required channels using Fisher Discriminant Ratio function. The experimental study showed that 27 optimal channels were sufficient to yield an average classification rate of 90.97% across 800 test VEP patterns from 40 subjects. Being fewer in number than 61 channels, it is less cumbersome, requires lower computational time, design complexity and cost. This was achieved without loss of performance as 61 channels gave an average classification result of 89.11%. The positive results obtained here showed that the neural activity during perception of visual stimulus was different across individuals. This method could be explored further as a biometric tool to identify individuals as the brain signals are difficult to be forged.

Item Type: Article
DOI/Identification number: 10.3233/KES-2006-10604
Additional information: Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - Int. J. Knowledge-Based Intell. Eng. Syst. [Field not mapped to EPrints] AD - School of Information and Communications Technology, Republic Polytechnic, 738964, Singapore [Field not mapped to EPrints] AD - Faculty of Information Science and Technology, Multimedia University, Melaka, 75450, Malaysia [Field not mapped to EPrints] AD - Department of Computer Science, University of Essex, Colchester, CO4 3SQ, United Kingdom [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Article [Field not mapped to EPrints]
Uncontrolled keywords: Fisher discriminant ratio, Gamma band power, Individual identification, Neural network, Optimal channels, Visual evoked potential
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 19:27 UTC
Last Modified: 30 May 2019 08:29 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70736 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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