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Even-related EEG/MEG synchronization and desynchronization: Basis principles
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Brain-computer interface-a new communication decive for handicapped persons
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Frequency component selection for an EEG-based brain computer interface
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Design and operation of an EEG-based brain-computer interface with digital signal processing technology
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Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters
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G. Pfurtscheller, C. Neuper, A. Schlogl, and K. Lugger, "Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters," IEEE Trans. Rehabilitation Engineering, vol.6, pp.316-325, Sep. 1998.
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Classification of single trial motor imagery EEG recordings with subject adapted non-dyadic arbitrary time-frequency tilings
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Extraction subject-specific motor imagery time-frequency patterns for single trial EEG classification
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Noninvasive brain-actuated control of a mobile robot by human EEG
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Asynchronous non-invasive brain-actuated control of an intelligent wheelchair
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A novel design of 4-class BCI using two binary classifiers and parallel mental tasks
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13
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Information transfer rate in a five-classes brain-computer interface
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B. Obermaier, C. Neuper, C. Guger, and G. Pfurtscheller, "Information transfer rate in a five-classes brain-computer interface," IEEE Trans. Neural Systems and Rehabilitation Engineering, vol.9, no.3, pp.283-288, 2001.
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Obermaier, B.1
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33747585373
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Seperability of four-class motor imagery data using independent components analysis
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M. Naeem, C. Brunner, R. Leeb, B. Graimann, and G. Pfurtscheller, "Seperability of four-class motor imagery data using independent components analysis," Journal of Neural Engineering, vol.3, no.3, pp.208-216, 2006.
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Journal of Neural Engineering
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Naeem, M.1
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