Abstract
A research on biometry based on human brain activities has lately become attracted and emerging. In this study, we investigate the feasibility of personal identification based on photo retrieval using three-channel electroencephalogram. Nine photo images were randomly presented one after another to five subjects without training. The Principal Component Analysis and the Linear Discriminant Analysis were applied to perform the simulation of the personal identification. The algorithm correctly identified 82.5, 93.0, and 100.0 % of the subject using EEG activities with 5, 10, and 20-times averaging, respectively. This study reveals a future possibility of photo retrieval tasks to realize the personal identification system using human brain activities, which will yield rich controls of machine for the users of brain-computer interface.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain computer interfaces for communication and control. Clinical Neurophysiology 113(6), 767–791 (2002)
Pfurtscheller, G., Neuper, C.: Motor imagery activates primary sensorimotor area in humans. Neurosci. Lett. 239(2-3), 65–68 (1997)
Blankertz, B., Dornhege, G., Krauledat, M., Muller, K.R., Kunzmann, V., Losch, F., Curio, G.: The Berlin Brain-Computer Interface: EEG-based communication without subject training. IEEE Trans Neural Syst. Rehabil. Eng. 14(2), 147–152 (2006)
Middendorf, M., McMillan, G., Calhoun, G., Jones, K.S.: Brain-Computer Interfaces Based on the Steady-State Visual-Evoked Response. IEEE Transactions on Rehabilitation Engineering 8(2), 211–214 (2000)
Cheng, M., Gao, X., Gao, S., Xu, D.: Design and Implementation of a Brain-Computer Interface With High Transfer Rates. IEEE Transactions on Biomedical Engineering 49(10), 1181–1186 (2002)
Farwell, L.A., Donchin, E.: Taking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr. Clin. Neurophysiol. 70(6), 510–523 (1988)
Bayliss, J.D.: The use of the evoked potential P3 component for control in a virtual apartment. IEEE Transaction on Neural Systems and Rehabilitation Engineering 11(2), 113–116 (2003)
Marcel, S., Millan, J.R.: Person authentication using brainwaves (EEG) and maximum a posteriori model adaptation. IEEE Transaction on pattern analysis and machine intelligence 29(4), 743–752 (2007)
Paranjape, R.B., Mahovsky, J., Benedicenti, L., Koles, Z.: The Electroencephalogram as a Biometric. In: Proc. of Canadian Conf. on Electrical and Computer Eng., vol. 2, pp. 1363–1366 (2001)
Poulos, M., Rangoussi, M.: Parametric person identification from the EEG using computational geometry. In: Proc. of the Sixth Int’l Conf. on Electronics, Circuits, and Systems, vol. 2, pp. 1005–1012 (1999)
Palaniappan, R., Mandic, D.P.: Biometrics from brain electrical activity: a machine learning approach. IEEE Transaction on pattern analysis and machine intelligence 29(4), 738–742 (2007)
Thorpe, J., van Oorschot, P.C., Somayaji, A.: Pass-thoughts: Authenticating With Our Minds. In: Proc. of ACSA 2005 New Security Paradigms Workshop (2005)
(The photo images in this study were downloaded only for the research purpose), See the website, http://www.flickr.com/
Krusienski, D.J., Sellers, E.W., McFarland, D.J., Vaughan, T.M., Wolpaw, J.R.: Toward enhanced P300 speller performance. J. Neurosci. Methods 167(1), 15–21 (2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Touyama, H., Hirose, M. (2008). The Use of Photo Retrieval for EEG-Based Personal Identification. In: Lee, S., Choo, H., Ha, S., Shin, I.C. (eds) Computer-Human Interaction. APCHI 2008. Lecture Notes in Computer Science, vol 5068. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70585-7_31
Download citation
DOI: https://doi.org/10.1007/978-3-540-70585-7_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70584-0
Online ISBN: 978-3-540-70585-7
eBook Packages: Computer ScienceComputer Science (R0)