Individual identification technique using visual evoked potential signals

Palaniappan, Ramaswamy, Raveendran, P. (2002) Individual identification technique using visual evoked potential signals. Electronics Letters, 38 (25). pp. 1634-1635. ISSN 0013-5194. (doi:10.1049/el:20021104) (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) (KAR id:70759)

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.
Official URL: http://dx.doi.org/10.1049/el:20021104

Abstract

A new individual identification technique using visual evoked potential (VEP) signals is proposed. The technique uses fuzzy ARTMAP (FA) classification of gamma band VEP response from 61 channels extracted while the individual is seeing a single picture. All ten subjects tested are classified correctly with an overall maximum classification rate of 95% across 200 test patterns. The method could be developed into a stand-alone identification system or as an addition to existing identification systems, especially for identifying a group of individuals in a company or factory.

Item Type:	Article
DOI/Identification number:	10.1049/el:20021104
Additional information:	Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - Electron. Lett. [Field not mapped to EPrints] AD - Faculty of Info. Sci. and Technol., Multimedia University, Jalan Ayer Keroh Lama, 75450 Melaka, Malaysia [Field not mapped to EPrints] AD - Electrical Department, Engineering Faculty, University Malaya, Kuala Lumpur 50603, Malaysia [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Article [Field not mapped to EPrints]
Uncontrolled keywords:	Bandpass filters, Bioelectric potentials, Equivalence classes, Frequency domain analysis, Fuzzy sets, High pass filters, Low pass filters, Neural networks, Time domain analysis, Fuzzy classification, Visual evoked potential, Pattern recognition
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User:	Palaniappan Ramaswamy
Date Deposited:	15 Dec 2018 17:25 UTC
Last Modified:	05 Nov 2024 12:33 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/70759 (The current URI for this page, for reference purposes)

University of Kent Author Information

Palaniappan, Ramaswamy.

Creator's ORCID:	https://orcid.org/0000-0001-5296-8396
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