Abstract
The on-line update of classifiers is an important concern for categorizing the time-varying neurophysiological signals used in brain computer interfaces, e.g. classification of electroencephalographic (EEG) signals. However, up to the present there is not much work dealing with this issue. In this paper, we propose to use the idea of gradient decorrelation to develop the existent basic Least Mean Square (LMS) algorithm for the on-line learning of Bayesian classifiers employed in brain computer interfaces. Under the framework of Gaussian mixture model, we give the detailed representation of Decorrelated Least Mean Square (DLMS) algorithm for updating Bayesian classifiers. Experimental results of off-line analysis for classification of real EEG signals show the superiority of the on-line Bayesian classifier using DLMS algorithm to that using LMS algorithm.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Nicolelis, M.A.L.: Actions from Thoughts. Nature 409, 403–407 (2001)
Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-Computer Interfaces for Communication and Control. Clinical Neurophysiology 113, 767–791 (2002)
Vaughan, T.M.: Guest Editorial Brain-Computer Interface Technology: A Review of the Second International Meeting. IEEE Transactions on Neural Systems and Rehabilitation Engineering 11, 94–109 (2003)
Ebrahimi, T., Vesin, J.M., Garcia, G.: Brain-Computer Interfaces in Multimedia Communication. IEEE Signal Processing Magazine 20, 14–24 (2003)
Millán, J.R., Renkens, F., Mouriño, J., Gerstner, W.: Non-Invasive Brain-Actuated Control of a Mobile Robot. In: Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, pp. 1121–1126 (2003)
Millán, J.R., Renkens, F., Mouriño, J., Gerstner, W.: Brain-Actuated Interaction. Artificial Intelligence 159, 241–259 (2004)
Millán, J.R., Renkens, F., Mouriño, J., Gerstner, W.: Noninvasive Brain-Actuated Control of a Mobile Robot by Human EEG. IEEE Transactions on Biomedical Engineering 51, 1026–1033 (2004)
Doherty, J., Porayath, R.: A Robust Echo Canceler for Acoustic Environments. IEEE Transactions on Circuits and Systems, II 44, 389–398 (1997)
Blankertz, B., Curio, G., Müller, K.R.: Classifying Single Trial EEG: Towards Brain Computer Interfacing. In: Dietterich, T.G., Becker, S., Ghaharamani, Z. (eds.) Advances in Neural Information Processing Systems, pp. 157–164. MIT Press, Cambridge (2002)
Wang, Y., Zhang, Z., Li, Y., Gao, X., Gao, S., Yang, F.: BCI Competition 2003-Data Set IV: An Algorithm Based on CSSD and FDA for Classifying Single-Trial EEG. IEEE Transactions on Biomedical Engineering 51, 1081–1086 (2004)
Kaper, M., Meinicke, P., Grossekathoefer, U., Lingener, T., Ritter, H.: BCI Competition 2003-Data Set IIb: Support Vector Machines for the P300 Speller Paradigm. IEEE Transactions on Biomedical Engineering 51, 1073–1076 (2004)
Lu, B., Shin, J., Ichikawa, M.: Massively Parallel Classifiation of Single-Trial EEG Signals Using a Min-Max Modular Neural Network. IEEE Transactions on Biomedical Engineering 51, 551–558 (2004)
Mclachlan, G., Peel, D.: Finite Mixture Models. Wiley, New York (2000)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. John Wiley & Sons, New York (2000)
Glentis, G.O., Berberidis, K., Theodoridis, S.: Efficient Least Square Adaptive Algorithms for FIR Transversal Filtering. IEEE Signal Processing Magzine 16, 13–41 (1999)
Perrin, R., Pernier, J., Bertrand, O., Echallier, J.: Spherical Spline for Potential and Current Density Mapping. Electroencephalography and Clinical Neurophysiology 72, 184–187 (1989)
Perrin, R., Pernier, J., Bertrand, O., Echallier, J.: Corrigendum EEG 02274. Electroencephalography and Clinical Neurophysiology 76, 565 (1990)
McFarland, D.J., McCane, L.M., David, S.V., Wolpaw, J.R.: Spatial Filter Selection for EEG-Based Communication. Electroencephalography and Clinical Neurophysiology 103, 386–394 (1997)
Millán, J.R.: On the Need for On-Line Learning in Brain-Computer Interfaces. In: Proceedings of 2004 International Joint Conference on Neural Networks, Budapest, Hungary (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sun, S., Zhang, C., Lu, N. (2005). On the On-line Learning Algorithms for EEG Signal Classification in Brain Computer Interfaces. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_79
Download citation
DOI: https://doi.org/10.1007/11540007_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
Online ISBN: 978-3-540-31828-6
eBook Packages: Computer ScienceComputer Science (R0)