An integrated hierarchical gaussian mixture model to estimate vigilance level based on EEG recordings
作者： Jing-Nan Gu , Hong-Jun Liu , Hong-Tao Lu , Bao-Liang Lu
DOI: 10.1007/978-3-642-24955-6_46
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摘要: Effective vigilance level estimation can be used to prevent disastrous accident occurred frequently in high-risk tasks. Brain Computer Interface(BCI) based on ElectroEncephalo-Graph(EEG) is a relatively reliable and convenient mechanism reflect one's psychological phenomena. In this paper we propose new integrated approach predict human level, which incorporate an automatically artifact removing pre-process, novel quantification method finally hierarchical Gaussian Mixed Model(hGMM) discover the underlying pattern of EEG signals. A reasonable high classification performance (88.46% over 12 data sets) obtained using approach. The hGMM proved more powerful against Support Vector Machine(SVM) Linear Discriminant Analysis(LDA) under complicated probability distributions.
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Ian T. Nabney, Netlab: Algorithms for Pattern Recognition ,(2002)
G Bartels, Li-Chen Shi, Bao-Liang Lu, Automatic artifact removal from EEG - a mixed approach based on double blind source separation and support vector machine international conference of the ieee engineering in medicine and biology society. ,vol. 2010, pp. 5383- 5386 ,(2010) , 10.1109/IEMBS.2010.5626481
A Belyavin, Nicola A Wright, Changes in electrical activity of the brain with vigilance Electroencephalography and Clinical Neurophysiology. ,vol. 66, pp. 137- 144 ,(1987) , 10.1016/0013-4694(87)90183-0
Li-Chen Shi, Hong Yu, Bao-Liang Lu, Semi-Supervised Clustering for Vigilance Analysis Based on EEG international joint conference on neural network. pp. 1518- 1523 ,(2007) , 10.1109/IJCNN.2007.4371183
H Fruhstorfer, R.M Bergström, Human vigilance and auditory evoked responses Electroencephalography and Clinical Neurophysiology. ,vol. 27, pp. 346- 355 ,(1969) , 10.1016/0013-4694(69)91443-6
Benjamin Blankertz, Guido Dornhege, Gabriel Curio, Klaus-Robert Müller, Combining Features for BCI neural information processing systems. ,vol. 15, pp. 1139- 1146 ,(2002)
Jonathan R Wolpaw, Niels Birbaumer, Dennis J McFarland, Gert Pfurtscheller, Theresa M Vaughan, Brain-computer interfaces for communication and control. Clinical Neurophysiology. ,vol. 113, pp. 767- 791 ,(2002) , 10.1016/S1388-2457(02)00057-3
Carl Edward Rasmussen, The Infinite Gaussian Mixture Model neural information processing systems. ,vol. 12, pp. 554- 560 ,(1999)
Mehrdad Fatourechi, Ali Bashashati, Rabab K. Ward, Gary E. Birch, EMG and EOG artifacts in brain computer interface systems: A survey Clinical Neurophysiology. ,vol. 118, pp. 480- 494 ,(2007) , 10.1016/J.CLINPH.2006.10.019
H. Ramoser, J. Muller-Gerking, G. Pfurtscheller, Optimal spatial filtering of single trial EEG during imagined hand movement international conference of the ieee engineering in medicine and biology society. ,vol. 8, pp. 441- 446 ,(2000) , 10.1109/86.895946