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The single-channel dry electrode SSVEP-based biometric approach: data augmentation techniques against overfitting for

Kutlucan Gorur1, Beyza Eraslan2

  • 1Electrical and Electronics Engineering, Bandirma Onyedi Eylul University, 10200, Balikesir, Turkey. kgorur@bandirma.edu.tr.

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|November 1, 2022
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Summary

This study introduces a novel, user-friendly biometric system using steady-state visually evoked potentials (SSVEP) and Recurrent Neural Networks (RNNs). The system achieves high accuracy for individual identification, offering a low-cost authentication solution.

Keywords:
BiometricData augmentation techniquesRecurrent neural networksSSVEPSingle-channel

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Area of Science:

  • Biometrics
  • Neuroscience
  • Signal Processing

Background:

  • Traditional electroencephalography (EEG) biometrics face challenges like noise and effort.
  • Steady-state visually evoked potential (SSVEP) biometrics offer a high signal-to-noise ratio and require no user training.

Purpose of the Study:

  • To compare multi-channel SSVEP biometrics with a novel single-channel, single-trial SSVEP approach using Recurrent Neural Networks (RNNs).
  • To evaluate the efficacy of data augmentation strategies with RNNs for SSVEP-based biometrics to prevent overfitting.

Main Methods:

  • Implementation of a single-channel, single-trial SSVEP biometric system utilizing dry electrodes.
  • Application of Recurrent Neural Networks (RNNs) with data augmentation for biometric recognition.
  • Performance evaluation using accuracy, sensitivity, specificity, and F-scores.

Main Results:

  • The single-channel SSVEP-based biometric system achieved up to 100% accuracy.
  • Sensitivity and specificity scores exceeded 97%, with F-scores also above 97% for 11 subjects.
  • The RNN deep models demonstrated promising results for individual identification.

Conclusions:

  • The proposed single-channel SSVEP biometric approach using RNNs is a low-cost, user-friendly, and reliable method for individual identification.
  • This technique has potential for significant applications in authentication and security systems.