Biometric Authentication with Electroencephalograms: Evaluation of Its Suitability Using Visual Evoked Potentials

  • André Zúquete
  • Bruno Quintela
  • João Paulo Silva Cunha
Part of the Communications in Computer and Information Science book series (CCIS, volume 127)


This paper studies the suitability of brain activity, namely electroencephalogram signals, as raw material for conducting biometric authentication of individuals. Brain responses were extracted in particular scenarios, namely with visual stimulation leading to biological brain responses known as visual evoked potentials. In our study, we evaluated a novel method, using only 8 occipital electrodes and the energy of differential EEG signals, to extract information about the subjects for further use as their biometric features. To classify the features obtained from each individual we used a one-class classifier per subject. These classifiers are trained only with target class features, which is the correct procedure to apply in biometric authentication scenarios. Two types of one-class classifiers were tested, K-Nearest Neighbor and Support Vector Data Description. Two other classifier architectures were also studied, both resulting from the combination of the two previously mentioned classifiers. After testing these classifiers with the features extracted from 70 subjects, the results showed that brain responses to visual stimuli are suitable for an accurate biometric authentication.


Area Under Curve Visual Evoke Potential Authentication System Biometric Authentication Common Spatial Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • André Zúquete
    • 1
  • Bruno Quintela
    • 2
  • João Paulo Silva Cunha
    • 1
  1. 1.IEETA / University of AveiroAveiroPortugal
  2. 2.University of AveiroAveiroPortugal

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