Graz brain-computer interface II: towards communication between humans and computers based on online classification of three different EEG patterns.
作者： J. Kalcher , D. Flotzinger , Ch. Neuper , S. Gölly , G. Pfurtscheller
DOI: 10.1007/BF02520010
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摘要: The paper describes work on the brain-computer interface (BCI). BCI is designed to help patients with severe motor impairment (e.g. amyotropic lateral sclerosis) communicate their environment through wilful modification of EEG. To establish such a communication channel, two major prerequisites have be fulfilled: features that reliably describe several distinctive brain states available, and these must classified on-line, i.e. single-trial basis. prototype Graz II, which based distinction three different types EEG pattern, described, results online offline classification performance four subjects are reported. suggest that, in best case, accuracy about 60% reached after only training sessions. show how selection specific frequency bands influences singletrial data.
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D. Flotzinger, G. Pfurtscheller, Ch. Neuper, J. Berger, W. Mohl, Classification of non-averaged eeg data by learning vector quantization and the impact of signal preprocessing international conference of the ieee engineering in medicine and biology society. ,vol. 32, pp. 571- 576 ,(1993) , 10.1007/BF02515317
Jonathan R. Wolpaw, Dennis J. McFarland, Gregory W. Neat, Richard F. Read, An EEG-based method for graded cursor control Psychobiology. ,vol. 21, pp. 77- 81 ,(1993) , 10.3758/BF03327130
M. Pregenzer, G. Pfurtscheller, D. Flotzinger, Automated feature selection with a distinction sensitive learning vector quantizer Neurocomputing. ,vol. 11, pp. 19- 29 ,(1996) , 10.1016/0925-2312(94)00071-9
W. Klimesch, H. Schimke, J. Schwaiger, Episodic and semantic memory: an analysis in the EEG theta and alpha band Electroencephalography and Clinical Neurophysiology. ,vol. 91, pp. 428- 441 ,(1994) , 10.1016/0013-4694(94)90164-3
Jonathan R. Wolpaw, Dennis J. McFarland, Multichannel EEG-based brain-computer communication Electroencephalography and Clinical Neurophysiology. ,vol. 90, pp. 444- 449 ,(1994) , 10.1016/0013-4694(94)90135-X
T. Kohonen, The self-organizing map Proceedings of the IEEE. ,vol. 78, pp. 1464- 1480 ,(1990) , 10.1109/5.58325
G. Pfurtscheller, D. Flotzinger, W. Mohl, M. Peltoranta, Prediction of the side of hand movements from single-trial multi-channel EEG data using neural networks. Electroencephalography and Clinical Neurophysiology. ,vol. 82, pp. 313- 315 ,(1992) , 10.1016/0013-4694(92)90112-U
A. Hiraiwa, K. Shimohara, Y. Tokunaga, EEG topography recognition by neural networks IEEE Engineering in Medicine and Biology Magazine. ,vol. 9, pp. 39- 42 ,(1990) , 10.1109/51.59211
G. Pfurtscheller, M. Pregenzer, C. Neuper, Visualization of sensorimotor areas involved in preparation for hand movement based on classification of μ and central β rhythms in single EEG trials in man Neuroscience Letters. ,vol. 181, pp. 43- 46 ,(1994) , 10.1016/0304-3940(94)90556-8
Jonathan R. Wolpaw, Dennis J. McFarland, Gregory W. Neat, Catherine A. Forneris, An EEG-based brain-computer interface for cursor control Electroencephalography and Clinical Neurophysiology. ,vol. 78, pp. 252- 259 ,(1991) , 10.1016/0013-4694(91)90040-B