NDLI: Multichannel EEG-based biometric using improved RBF neural networks

Content Provider	IEEE Xplore Digital Library
Author	Gui, Qiong Jin, Zhanpeng Xu, Wenyao Ruiz-Blondet, Maria V. Laszlo, Sarah
Copyright Year	2015
Description	Author affiliation: Dept of Electrical and Computer Engineering, Binghamton University, SUNY, NY 13902-6000, USA (Gui, Qiong; Jin, Zhanpeng) \|\| Dept of Computer Science and Engineering, University at Buffalo, SUNY, NY 14260-2500, USA (Xu, Wenyao) \|\| Dept. of Psychology, Binghamton University, SUNY, NY 13902-6000, USA (Ruiz-Blondet, Maria V.; Laszlo, Sarah)
Abstract	Electroencephalogram (EEG) brainwaves have recently emerged as a promising biometric that can be used for individual identification. In this study, we present a new visual stimuli-driven, non-volitional brain responses based methodological framework towards individual identification. The non-volitional mechanism provides an even more secure way in which the individuals are not aware of security credentials and thus can not manipulate their brain activities. Given the intercorrelated structure of brain functional areas, instead of making the identification decision relying on any single EEG channel, we propose a new identification approach based on the decision-level fusion of multichannel EEG signals, using the Radial Basis Function (RBF) neural network and its improved versions. Specifically, the identification decision is determined according to the identification patterns reflected from multiple EEG channels over the desired brain functional region. We evaluate the performance of our proposed methods based on four different visual stimuli and four independent EEG channels. Experimental results show that, the proposed fusion technique can significantly improve the identification accuracy, compared to the conventional single channel based solution. For RBF network, the accuracy of identifying 37 subjects could reach over 70%, which is better than the average accuracy of about 55% achieved through individual channels. For the improved RBF networks, the frequency-based decision making could reach the accuracy of 90%, while the probability-based method could reach over 91%. Our study lays a foundation for future investigation of more accurate and reliable brainwave-based biometrics.
Starting Page	1
Ending Page	6
File Size	207016
Page Count	6
File Format	PDF
ISBN	9781509013500
DOI	10.1109/SPMB.2015.7405418
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Neurons Radial basis function networks Feature extraction Electroencephalography Biological neural networks
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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