Multifeature biometric system based on EEG signals

Authors:
Hu Jian-feng
Affiliations:
Jiangxi Bluesky University, Nanchang, Jiangxi, China
Venue:
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Year:
2009

Citing 3
Cited 0

Biometrics from Brain Electrical Activity: A Machine Learning Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence
Person Authentication Using Brainwaves (EEG) and Maximum A Posteriori Model Adaptation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Unobtrusive biometric system based on electroencephalogram analysis

EURASIP Journal on Advances in Signal Processing

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Abstract

This paper focuses on the person authentication problem based on EEG signals. Many features extracted from EEG recordings have proved to be unique enough among subjects for biometric application. However, different features show different discriminative power for different subjects and different trials. We present here an authentication system, which make use of a multifeature fusion architecture. The results demonstrate to improve the system performance. Depending on the security level, different thresholds can be applied. The influence of different thresholds on system performance is discussed.