Home // INTELLI 2016, The Fifth International Conference on Intelligent Systems and Applications // View article

Individual Identification Using EEG Features

Authors:
Mona Fatma Ahmed
May Salama
Ahmed Sleman

Keywords: EEG; identification; biometrics; brain-waves;

Abstract:
Electroencephalography (EEG) is a method of monitoring electrical activity along the scalp by measuring voltage variations resulting from neural activity of the brain. A number of published research papers have indicated that there is enough individuality in the EEG recording, rendering it suitable as a tool for person authentication. In recent years there has been a growing need for greater security for person authentication and one of the potential solutions is to employ the innovative biometric authentication techniques. In this research paper, we investigate the possibility of person identification based on features extracted from person’s measured brain signals electrical activity (EEG) with different classification techniques; Radial Basis Functions (RBF), Support Vector Machines (SVM) and Backpropagation (BP) neural networks. The highest identification accuracy was achieved using modular backpropagation neural network for classification.

Pages: 26 to 29

Copyright: Copyright (c) IARIA, 2016

Publication date: November 13, 2016

Published in: conference

ISSN: 2308-4065

ISBN: 978-1-61208-518-0

Location: Barcelona, Spain

Dates: from November 13, 2016 to November 17, 2016