Electroencephalography biometric authentication using eye blink artifacts

This study presents a novel approach to electroencephalography (EEG) biometric authentication using eye blink artifacts. Unlike traditional methods that rely on imagination and mental tasks, which are susceptible to emotional and physical variations, this approach leverages the consistent effects of eye blinks on brainwaves for authentication. Brainwaves were recorded using the NeuroSky Mindwave Mobile 2 headset, and eye blinks were extracted via NeuroSky’s blink detection algorithm. An authentication algorithm was developed based on blink strength, time, and frequency. The proposed method demonstrated high performance with an accuracy (ACC) of 97%, a false acceptance rate (FAR) of 5%, and a false rejection rate (FRR) of 1%. This study also explored the impact of emotions and physical exercise on the authentication process, confirming the method's robustness under varying conditions. These findings suggest that eye blink artifacts offer a reliable and practical biometric trait for EEG-based authentication systems, providing a secure alternative to traditional biometric methods. The substantial contribution of this research lies in demonstrating the superior stability and usability of eye blink-based EEG authentication under diverse conditions, compared to existing EEG authentication methods that often require mental tasks or multi-channel recordings.

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Publication Details

Journal
Indonesian Journal of Electrical Engineering and Computer Science
Published
2024-08-30
DOI
https://doi.org/10.11591/ijeecs.v36.i2.pp872-881
Citations
2
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
0.74
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article

Electroencephalography biometric authentication using eye blink artifacts

Irina Zlotnikova, Hlomani Hlomani, Thamang Teddy Madile
2 citations
Indonesian Journal of Electrical Engineering and Computer Science
Gaze Tracking and Assistive Technology
0.74
article

Electroencephalography biometric authentication using eye blink artifacts

Irina Zlotnikova, Hlomani Hlomani, Thamang Teddy Madile
article en
2 citations

Abstract

This study presents a novel approach to electroencephalography (EEG) biometric authentication using eye blink artifacts. Unlike traditional methods that rely on imagination and mental tasks, which are susceptible to emotional and physical variations, this approach leverages the consistent effects of eye blinks on brainwaves for authentication. Brainwaves were recorded using the NeuroSky Mindwave Mobile 2 headset, and eye blinks were extracted via NeuroSky’s blink detection algorithm. An authentication algorithm was developed based on blink strength, time, and frequency. The proposed method demonstrated high performance with an accuracy (ACC) of 97%, a false acceptance rate (FAR) of 5%, and a false rejection rate (FRR) of 1%. This study also explored the impact of emotions and physical exercise on the authentication process, confirming the method's robustness under varying conditions. These findings suggest that eye blink artifacts offer a reliable and practical biometric trait for EEG-based authentication systems, providing a secure alternative to traditional biometric methods. The substantial contribution of this research lies in demonstrating the superior stability and usability of eye blink-based EEG authentication under diverse conditions, compared to existing EEG authentication methods that often require mental tasks or multi-channel recordings.

Indonesian Journal of Electrical Engineering and Computer ScienceVol. 36(2)
Botswana International University of Science and Technology (BW), Botswana Geoscience Institute (BW)
Openalex Percentile: Top 29%
Gaze Tracking and Assistive Technology
0.74
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Electroencephalography biometric authentication using eye blink artifacts — Irina Zlotnikova, Hlomani Hlomani, et al. · Indonesian Journal of Electrical Engineering and Computer Science (2024) | TGRS Research Map | TGRS