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Identifying individuality using mental task based brain computer interface

Palaniappan, Ramaswamy (2005) Identifying individuality using mental task based brain computer interface. In: Proceedings of the 3rd International Conference on Intelligent Sensing and Information Processing. . pp. 239-242. IEEE ISBN 978-0-7803-9588-6. (doi:10.1109/ICISIP.2005.1619442) (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/ICISIP.2005.1619442

Abstract

In recent years, numerous Brain Computer Interface (BCI) technologies have been developed to assist the disabled. In this paper, mental task based BCI is proposed for a different purpose: to identify the individuality of a person. The idea is based on the classification of electroencephalogram (EEG) signals recorded when a user thinks of either one or two mental tasks. As different individuals have different thought processes, this idea would be appropriate for individual identification. To increase the inter-subject differences, EEG data from six electrodes are used instead of one. Sixth order autoregressive features are computed from EEG signals and classified by Linear Discriminant classifier using a modified 10 fold cross validation procedure, which gave an average error of 0.95% when tested on 400 EEG patterns from four subjects. Though the method would have to undergo further development to obtain repeatable good accuracy; this initial study has shown the huge potential of the method over existing biometric identification systems as it is impossible to be faked.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/ICISIP.2005.1619442
Additional information: Unmapped bibliographic data: C7 - 1619442 [EPrints field already has value set] LA - English [Field not mapped to EPrints] J2 - Proc. - Int. Conf. Intell. Sens. Inf. Proc., ICISIP [Field not mapped to EPrints] AD - Dept. of Computer Science, University of Essex, Colchester, United Kingdom [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] A4 - [Field not mapped to EPrints] C3 - Proceedings - 3rd International Conference on Intelligent Sensing and Information Processing, ICISIP 2005 [Field not mapped to EPrints]
Uncontrolled keywords: Biometrics, Brain computer interfaces, Brain modeling, Computer interfaces, Electrodes, Electroencephalography, Fingerprint recognition, Geometry, Linear discriminant analysis, Testing, Biomedical signal processing, Biometrics, Brain models, Discriminant analysis, Electrodes, Electroencephalography, Electrophysiology, Geometry, Interfaces (computer), Pattern recognition, Testing, 10-fold cross-validation, Autoregressive features, Biometric identification systems, Electroencephalogram signals, Fingerprint Recognition, Individual identification, Linear discriminant analysis, Linear discriminant classifier, Brain computer interface
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 16:54 UTC
Last Modified: 30 May 2019 08:29 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70749 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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