Abstract
The use of brain-wave patterns extracted from electroencephalography (EEG) brain signals for person verification has been investigated recently. The challenge is that the EEG signals are noisy due to low conductivity of the human skull and the EEG data have unknown distribution. We propose a multi-sphere support vector data description (MSSVDD) method to reduce noise and to provide a mixture of hyperspheres that can describe the EEG data distribution. We also propose a MSSVDD universal background model (UBM) to model impostors in person verification. Experimental results show that our proposed methods achieved lower verification error rates than other verification methods.
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References
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)
Xu, Q., Zhou, H., Wang, Y., Huang, J.: Fuzzy support vector machine for classification of EEG signals using wavelet-based features. Medical Engineering & Physics 31(7), 858–865 (2009)
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)
Poulos, M., Rangoussi, M., Alexandris, N., Evangelou, A.: Person identification from the EEG using nonlinear signal classification. Methods of Information in Medicine 41(1), 64–75 (2002)
Palaniappan, R.: Two-stage biometric authentication method using thought activity brain waves. International Journal of Neural Systems 18(1), 59 (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 (2009)
Lotte, F., Congedo, M., Lécuyer, A., Lamarche, F., Arnaldi, B.: A review of classification algorithms for EEG-based brain computer interfaces. Journal of Neural Engineering 4, R1 (2007)
Zúquete, A., Quintela, B., Cunha, J.P.S.: Biometric authentication using brain responses to visual stimuli. In: Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, pp. 103–112 (2010)
Bimbot, F., Bonastre, J.F., Fredouille, C., Gravier, G., Magrin-Chagnolleau, I., Meignier, S., Merlin, T., Ortega-García, J., Petrovska-Delacrétaz, D., Reynolds, D.A.: A tutorial on text-independent speaker verification. EURASIP Journal on Applied Signal Processing 2004, 430–451 (2004)
Reynolds, D.A., Quatieri, T.F., Dunn, R.B.: Speaker verification using adapted gaussian mixture models. Digital Signal Processing 10(1), 19–41 (2000)
Campbell, W.M., Sturim, D.E., Reynolds, D.A.: Support vector machines using GMM supervectors for speaker verification. IEEE Signal Processing Letters 13(5), 308–311 (2006)
Brew, A., Grimaldi, M., Cunningham, P.: An evaluation of one-class classification techniques for speaker verification. Artificial Intelligence Review 27(4), 295–307 (2007)
Tran, D.T.: Fuzzy Approaches to Speech and Speaker Recognition. PhD thesis, University of Canberra (2000)
Hunter, M., Smith, R.L., Hyslop, W., Rosso, O.A., Gerlach, R., Rostas, J.A.P., Williams, D.B., Henskens, F.: The australian EEG database. Clin. EEG Neurosci. 36(2), 76–81 (2005)
Schalk, G., McFarland, D.J., Hinterberger, T., Birbaumer, N., Wolpaw, J.R.: BCI2000: a general-purpose brain-computer interface (BCI) system. IEEE Transactions on Biomedical Engineering 51(6), 1034–1043 (2004)
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 (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 (2001)
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Nguyen, P., Tran, D., Le, T., Huang, X., Ma, W. (2013). EEG-Based Person Verification Using Multi-Sphere SVDD and UBM. In: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2013. Lecture Notes in Computer Science(), vol 7818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37453-1_24
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DOI: https://doi.org/10.1007/978-3-642-37453-1_24
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