Skip to main content

Two-stage biometric authentication method using thought activity brain waves

Palaniappan, Ramaswamy (2008) Two-stage biometric authentication method using thought activity brain waves. International Journal of Neural Systems, 18 (1). pp. 59-66. ISSN 0129-0657. (doi:10.1142/S0129065708001373) (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:70718)

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


Brain waves are proposed as a biometric for verification of the identities of individuals in a small group. The approach is based on a novel two-stage biometric authentication method that minimizes both false accept error (FAE) and false reject error (FRE). These brain waves (or electroencephalogram (EEG) signals) are recorded while the user performs either one or several thought activities. As different individuals have different thought processes, this idea would be appropriate for individual authentication. In this study, autoregressive coefficients, channel spectral powers, inter-hemispheric channel spectral power differences, inter-hemispheric channel linear complexity and non-linear complexity (approximate entropy) values were used as EEG features by the two-stage authentication method with a modified four fold cross validation procedure. The results indicated that perfect accuracy was obtained, i.e. the FRE and FAE were both zero when the proposed method was tested on five subjects using certain thought activities. This initial study has shown that the combination of the two-stage authentication method with EEG features from thought activities has good potential as a biometric as it is highly resistant to fraud. However, this is only a pilot type of study and further extensive research with more subjects would be necessary to establish the suitability of the proposed method for biometric applications. © 2008 World Scientific Publishing Company.

Item Type: Article
DOI/Identification number: 10.1142/S0129065708001373
Additional information: Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - Int. J. Neural Syst. [Field not mapped to EPrints] C2 - 18344223 [Field not mapped to EPrints] AD - Department of Computing and Electronic Systems, University of Essex, Colchester, CO4 3SQ, United Kingdom [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints]
Uncontrolled keywords: Authentication, Biometric, Electroencephalogram, Thought activities, Authentication, Brain models, Electroencephalography, Optimization, Spectrum analysis, Brain waves, False accept error (FAE), False reject error (FRE), Thought activities, Biometrics, animal, article, artificial intelligence, automated pattern recognition, biometry, brain, brain mapping, electroencephalography, human, physiology, Animals, Artificial Intelligence, Biometry, Brain, Brain Mapping, Electroencephalography, Humans, Pattern Recognition, Automated
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Palaniappan Ramaswamy
Date Deposited: 12 Dec 2018 22:26 UTC
Last Modified: 16 Nov 2021 10:25 UTC
Resource URI: (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy:
  • Depositors only (login required):