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EEG based biometric framework for automatic identity verification

Palaniappan, Ramaswamy, Mandic, Danilo P. (2007) EEG based biometric framework for automatic identity verification. Journal of Vlsi Signal Processing Systems for Signal Image and Video Technology, 49 (2). pp. 243-250. ISSN 0922-5773. (doi:10.1007/s11265-007-0078-1) (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:48263)

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
https://doi.org/10.1007/s11265-007-0078-1

Abstract

The energy of brain potentials evoked during processing of visual stimuli is considered as a new biometric. In particular, we propose several advances in the feature extraction and classification stages. This is achieved by performing spatial data/sensor fusion, whereby the component relevance is investigated by selecting maximum informative (EEG) electrodes (channels) selected by Davies–Bouldin index. For convenience and ease of cognitive processing, in the experiments, simple black and white drawings of common objects are used as visual stimuli. In the classification stage, the Elman neural network is employed to classify the generated EEG energy features. Simulations are conducted by using the hold-out classification strategy on an ensemble of 1,600 raw EEG signals, and 35 maximum informative channels achieved the maximum recognition rate of 98.56?±?1.87%. Overall, this study indicates the enormous potential of the EEG biometrics, especially due to its robustness against fraud.

Item Type: Article
DOI/Identification number: 10.1007/s11265-007-0078-1
Additional information: Unmapped bibliographic data: ST - EEG based biometric framework for automatic identity verification [Field not mapped to EPrints] AN - WOS:000249982900003 [Field not mapped to EPrints]
Uncontrolled keywords: biometric, Davies–Bouldin index, electroencephalogram, identity identification, neural network
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 10 Dec 2018 18:42 UTC
Last Modified: 29 May 2019 14:30 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/48263 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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