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Motor imagery EEG-based person verification
conference contribution
posted on 2013-01-01, 00:00 authored by Phuoc NguyenPhuoc Nguyen, D Tran, X Huang, W MaWe investigate in this paper the activity-dependent person verification method using electroencephalography (EEG) signal from a person performing motor imagery tasks. Two tasks were performed in our experiments were performed. In the first task, the same motor imagery task of left hand or right hand was applied to all persons. In the second task, only the best motor imagery task for each person was performed. The Gaussian mixture model (GMM) and support vector data description (SVDD) methods were used for modelling persons. Experimental results showed that lowest person verification error rate could be achieved when each person performed his/her best motor imagery task.
History
Event
Artificial Neural Networks. Conference (12th : 2013 : Puerto de la Cruz, Tenerife, Spain)Volume
7903Issue
Part 2Series
Artificial Neural Networks ConferencePagination
430 - 438Publisher
SpringerLocation
Puerto de la Cruz, Tenerife, SpainPlace of publication
Berlin, GermanyPublisher DOI
Start date
2013-06-12End date
2013-06-14ISSN
0302-9743eISSN
1611-3349ISBN-13
9783642386817Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2013, Springer-Verlag Berlin HeidelbergEditor/Contributor(s)
I Rojas, G Joya, J CabestanyTitle of proceedings
IWANN 2013 : Proceedings of the 12th International Work-Conference on Artificial Neural Networks 2013Usage metrics
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