Abstract
We 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
Original language | English |
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Title of host publication | International Work-Conference on Artificial Neural Networks |
Subtitle of host publication | Advances in Computational Intelligence IWANN 2013 |
Editors | Ignacio Rojas, Gonzalo Joya, Joan Gabestany |
Place of Publication | Berlin |
Publisher | Springer |
Pages | 430-438 |
Number of pages | 9 |
Volume | 2 |
ISBN (Electronic) | 9783642386824 |
ISBN (Print) | 9783642386817 |
DOIs | |
Publication status | Published - 2013 |
Event | 12th International Work-Conference on Artificial Neural Networks, IWANN 2013 - Tenerife, Tenerife, Spain Duration: 12 Jun 2013 → 14 Jun 2013 |
Conference
Conference | 12th International Work-Conference on Artificial Neural Networks, IWANN 2013 |
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Abbreviated title | IWANN 2013 |
Country/Territory | Spain |
City | Tenerife |
Period | 12/06/13 → 14/06/13 |