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Novel HHT-Based Features for Biometric Identification Using EEG Signals

Yang, Su, Deravi, Farzin (2014) Novel HHT-Based Features for Biometric Identification Using EEG Signals. In: International Conference on Pattern Recognition. ICPR 2014. . pp. 1922-1927. Institute of Electrical Electronic Engineers Computer Society (doi:10.1109/ICPR.2014.336) (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/10.1109/ICPR.2014.336

Abstract

In this paper we present a novel approach for biometric identification using electroencephalogram (EEG) signals based on features extracted with the Hilbert-Huang Transform (HHT). The instantaneous amplitude and the instantaneous frequency were computed after the HHT, and these were then used to generate the features for classification. The proposed system was evaluated using two publicly available databases in scenarios where only a single electrode is used to provide biometric information. One database (with 122 subjects) has the users viewing a series of pictures while the other one (with 109 subjects) has the users performing motor/imagery tasks. Average identification accuracies of 96% and 99% were reached for these two databases respectively using only a single electrode. These compare favourably with previously published results employing a variety of other features and classification approaches.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/ICPR.2014.336
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Tina Thompson
Date Deposited: 06 Jan 2015 09:33 UTC
Last Modified: 01 Aug 2019 10:38 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/46504 (The current URI for this page, for reference purposes)
Deravi, Farzin: https://orcid.org/0000-0003-0885-437X
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