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.
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Prabhakar, S., Kittler, J., Maltoni, D., O’Gorman, L., Tan, T.: Introduction to the special issue on biometrics: Progress and directions. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4), 513–516 (2007)
Riera, A., Soria-Frisch, A., Caparrini, M., Grau, C., Ruffini, G.: Unobtrusive biometric system based on electroencephalogram analysis. EURASIP Journal on Advances in Signal Processing 2008, 18 (2008)
Damousis, I.G., Tzovaras, D., Bekiaris, E.: Unobtrusive multimodal biometric authentication: the humabio project concept. EURASIP Journal on Advances in Signal Processing 2008, 110 (2008)
Marcel, S., Millán, J.R.: Person authentication using brainwaves (eeg) and maximum a posteriori model adaptation. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4), 743–752 (2007)
Palaniappan, R., Mandic, D.P.: Biometrics from brain electrical activity: A machine learning approach. IEEE Transactions 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: New Security Paradigms Workshop: Proceedings of the 2005 Workshop on New Security Paradigms, vol. 20, pp. 45–56 (2005)
Palaniappan, R.: Two-stage biometric authentication method using thought activity brain waves. International Journal of Neural Systems 18(01), 59–66 (2008)
He, C., Wang, J.: An independent component analysis (ica) based approach for eeg person authentication. In: 3rd International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2009, pp. 1–4. IEEE (2009)
Sanei, S., Chambers, J.A.: EEG signal processing. Wiley-Interscience (2007)
Stoica, P., Moses, R.L.: Spectral analysis of signals. Pearson/Prentice Hall (2005)
Tax, D.M.J., Duin, R.P.W.: Support vector data description. Machine Learning 54(1), 45–66 (2004)
Tran, D.T.: Fuzzy Approaches to Speech and Speaker Recognition. PhD thesis, university of Canberra (2000)
Leeb, R., Brunner, C., Müller-Putz, G.R., Schlögl, A., Pfurtscheller, G.: Bci competition 2008–graz data set b. In: Graz University of Technology, Austria (2008)
Poulos, M., Rangoussi, M., Chrissikopoulos, V., Evangelou, A.: Person identification based on parametric processing of the eeg. In: Proceedings of the 6th IEEE International Conference on Electronics, Circuits and Systems, ICECS 1999, vol. 1, pp. 283–286. IEEE (1999)
Paranjape, R.B., Mahovsky, J., Benedicenti, L., Koles, Z.: The electroencephalogram as a biometric. In: Canadian Conference on Electrical and Computer Engineering, vol. 2, pp. 1363–1366. IEEE (2001)
Martin, A., Doddington, G., Kamm, T., Ordowski, M., Przybocki, M.: The det curve in assessment of detection task performance. Technical report, DTIC Document (1997)
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Nguyen, P., Tran, D., Huang, X., Ma, W. (2013). Motor Imagery EEG-Based Person Verification. In: Rojas, I., Joya, G., Cabestany, J. (eds) Advances in Computational Intelligence. IWANN 2013. Lecture Notes in Computer Science, vol 7903. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38682-4_46
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DOI: https://doi.org/10.1007/978-3-642-38682-4_46
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