Abstract
An improved adaptive RBF neural network is proposed to realize the continuous classification of left and right hand motor imagery tasks. Leader-follower clustering is used to initialize the centers and variances of hidden layer neurons, which matches the time-variant input features. Based on the features of multichannel EEG complexity and field power, the time courses of two evaluating indexes i.e. classification accuracy and mutual information (MI) are calculated to obtain the maximum with 87.14% and 0.53bit respectively. The results show that the improved algorithm can provide the flexible initial centers of RBF neural network and could be considered for the continuous classification of mental tasks for BCI (Brain Computer Interface) application.
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References
Wolpaw, J.R., Birbaumer, N., McFarland, D.J., et al.: Brain-computer interfaces for communication and control. Clinical Neurophysilolgy, 767–791 (2002)
Pfurtscheller, G., Muller, G.R., Pfurtscheller, J.: ‘Thought’-control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia. Neurosci lett., 22–36 (2003)
Schlögl, A., Lugger, K., Pfurtscheller, G.: Using Adaptive Autoregressive Parameters for a Brain-Computer-Interface Experiment, EMBS, Chicago, USA, pp. 1533–1535 (1997)
Pfurtscheller, G., Lopes da Silva, F.H.: Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin. Neurophysiol., 1842–1857 (1999)
Wackermann, J.: Towards a quantitative characterization of functional states of the brain: from the non-linear methodology to the global linear description. Int. J. Psychophysiol., 65–80 (1999)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, China (2004)
Muller, K.R., Smola, A., Ratsch, G.: Using support vector machines for time series prediction. In: Advances in Kernel Methods-Support Vector Learning. MIT Press, Cambridge (1998)
Schlogl, A., Neuper, C., Pfurtscheller, G.: Estimating the mutual information of an EEG-based Brain-Computer-Interface. Biomedizinische Technik, 3–8 (2002)
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© 2005 Springer-Verlag Berlin Heidelberg
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Pei, Xm., Xu, J., Zheng, Cx., Bin, Gy. (2005). An Improved Adaptive RBF Network for Classification of Left and Right Hand Motor Imagery Tasks. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_136
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DOI: https://doi.org/10.1007/11539087_136
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28323-2
Online ISBN: 978-3-540-31853-8
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