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Unobtrusive Biometric System Based on Electroencephalogram Analysis

Abstract

Features extracted from electroencephalogram (EEG) recordings have proved to be unique enough between subjects for biometric applications. We show here that biometry based on these recordings offers a novel way to robustly authenticate or identify subjects. In this paper, we present a rapid and unobtrusive authentication method that only uses 2 frontal electrodes referenced to another one placed at the ear lobe. Moreover, the system makes use of a multistage fusion architecture, which demonstrates to improve the system performance. The performance analysis of the system presented in this paper stems from an experiment with 51 subjects and 36 intruders, where an equal error rate (EER) of 3.4% is obtained, that is, true acceptance rate (TAR) of 96.6% and a false acceptance rate (FAR) of 3.4%. The obtained performance measures improve the results of similar systems presented in earlier work.

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Correspondence to A. Riera.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Riera, A., Soria-Frisch, A., Caparrini, M. et al. Unobtrusive Biometric System Based on Electroencephalogram Analysis. EURASIP J. Adv. Signal Process. 2008, 143728 (2007). https://doi.org/10.1155/2008/143728

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Keywords

  • System Performance
  • Information Technology
  • Performance Analysis
  • Quantum Information
  • Acceptance Rate