Abstract
We propose a novel spectral filter optimization algorithm for the single trial ElectroEncephaloGraphy (EEG) classification problem. The algorithm is designed to improve the classification accuracy of Common Spatial Pattern (CSP) based classifiers. The algorithm is based on a simple statistical criterion, and allows the user to incorporate any prior information one has about the spectrum of the signal. We show that with a different preprocessing, how a prior knowledge can drastically improve the classification or only be misleading. We also show a generalization of the CSP algorithm so that the CSP spatial projection can be recalculated after the optimization of the spectral filter. This leads to an iterative procedure of spectral and spatial filter update that further improves the classification accuracy, not only by imposing a spectral filter but also by choosing a better spatial projection.
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References
Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113, 767–791 (2002)
Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler, A., Perelmouter, J., Taub, E., Flor, H.: A spelling device for the paralysed. Nature 398, 297–298 (1999)
Pfurtscheller, G., Neuper, C., Guger, C., Harkam, W., Ramoser, R., Schlögl, A., Obermaier, B., Pregenzer, M.: Current trends in Graz brain-computer interface (BCI). IEEE Trans. Rehab. Eng. 8(2), 216–219 (2000)
Blankertz, B., Dornhege, G., Schäfer, C., Krepki, R., Kohlmorgen, J., Müller, K.R., Kunzmann, V., Losch, F., Curio, G.: Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis. IEEE Trans. Neural Sys. Rehab. Eng. 11(2), 127–131 (2003)
Blankertz, B., Dornhege, G., Krauledat, M., Müller, K.R., Kunzmann, V., Losch, F., Curio, G.: The Berlin Brain-Computer Interface: EEG-based communication without subject training. IEEE Trans. Neural Sys. Rehab. Eng. 14(2) (in press, 2006)
Koles, Z.J.: The quantitative extraction and topographic mapping of the abnormal components in the clinical EEG. Electroencephalogr. Clin. Neurophysiol. 79, 440–447 (1991)
Ramoser, H., Müller-Gerking, J., Pfurtscheller, G.: Optimal spatial filtering of single trial EEG during imagined hand movement. IEEE Trans. Rehab. Eng. 8(4), 441–446 (2000)
Lemm, S., Blankertz, B., Curio, G., Müller, K.R.: Spatio-spectral filters for improved classification of single trial EEG. IEEE Trans. Biomed. Eng. 52(9), 1541–1548 (2005)
Dornhege, G., Blankertz, B., Krauledat, M., Losch, F., Curio, G., Müller, K.R.: Combined optimization of spatial and temporal filters for improving brain-computer interfacing. IEEE Trans. Biomed. Eng. (accepted, 2006)
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Tomioka, R., Dornhege, G., Nolte, G., Aihara, K., Müller, KR. (2006). Optimizing Spectral Filters for Single Trial EEG Classification. In: Franke, K., Müller, KR., Nickolay, B., Schäfer, R. (eds) Pattern Recognition. DAGM 2006. Lecture Notes in Computer Science, vol 4174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861898_42
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DOI: https://doi.org/10.1007/11861898_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44412-1
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