Publications
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Filters: Keyword is Humans and Author is Niels Birbaumer [Clear All Filters]
. Transition from the locked in to the completely locked-in state: a physiological analysis. Clin Neurophysiol [Internet]. 2011;122(5):925-33. http://www.ncbi.nlm.nih.gov/pubmed/20888292
Transition from the locked in to the completely locked-in state a physiological analysis.pdf (1.46 MB)
Transition from the locked in to the completely locked-in state a physiological analysis.pdf (1.46 MB). Voluntary brain regulation and communication with electrocorticogram signals. Epilepsy Behav [Internet]. 2008;13(2):300-6. http://www.ncbi.nlm.nih.gov/pubmed/18495541 Voluntary brain regulation and communication with electrocorticogram signals.pdf (1.45 MB)
Voluntary brain regulation and communication with electrocorticogram signals.pdf (1.45 MB). An MEG-based brain-computer interface (BCI). Neuroimage [Internet]. 2007;36(3):581-93. http://www.ncbi.nlm.nih.gov/pubmed/17475511 An MEG-based brain-computer interface (BCI).pdf (0 bytes)
An MEG-based brain-computer interface (BCI).pdf (0 bytes). The BCI competition III: Validating alternative approaches to actual BCI problems. IEEE Trans Neural Syst Rehabil Eng [Internet]. 2006;14(2):153-9. http://www.ncbi.nlm.nih.gov/pubmed/16792282 The BCI Competition III - Validating Alternative Approaches to Actual BCI Problems.pdf (0 bytes)
The BCI Competition III - Validating Alternative Approaches to Actual BCI Problems.pdf (0 bytes). Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects. IEEE Trans Neural Syst Rehabil Eng [Internet]. 2006;14(2):183-6. http://www.ncbi.nlm.nih.gov/pubmed/16792289 Classifying EEG and ECoG signals without subject training for fast BCI implementation comparison of nonparalyzed and completely paralyzed subjects.pdf (56.97 KB)
Classifying EEG and ECoG signals without subject training for fast BCI implementation comparison of nonparalyzed and completely paralyzed subjects.pdf (56.97 KB). Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. Neurology [Internet]. 2005;64(10):1775-7. http://www.ncbi.nlm.nih.gov/pubmed/15911809 Patients with ALS can use sensorimotor rhythms to operate a brain-comptuer interface.pdf (0 bytes)
Patients with ALS can use sensorimotor rhythms to operate a brain-comptuer interface.pdf (0 bytes). The BCI Competition 2003: Progress and perspectives in detection and discrimination of EEG single trials. IEEE Trans Biomed Eng. 2004;51(6):1044-51. The BCI Compeition 2003 - Progress and Perspectives in Detection and Discrimination of EEG Single Trials.pdf (0 bytes)
The BCI Compeition 2003 - Progress and Perspectives in Detection and Discrimination of EEG Single Trials.pdf (0 bytes). BCI2000: a general-purpose brain-computer interface (BCI) system. IEEE Trans Biomed Eng. 2004;51(6):1034-43. BCI2000 - A General-Purpose Brain-Computer Interface (BCI) System.pdf (0 bytes)
BCI2000 - A General-Purpose Brain-Computer Interface (BCI) System.pdf (0 bytes). Brain-computer interfaces for communication and control. Clin Neurophysiol [Internet]. 2002;113(6):767-91. http://www.ncbi.nlm.nih.gov/pubmed/12048038 Brain-computer interfaces for communication and control.pdf (519.69 KB)
Brain-computer interfaces for communication and control.pdf (519.69 KB). Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng [Internet]. 2000;8(2):164-73. http://www.ncbi.nlm.nih.gov/pubmed/10896178 Brain-Computer Interface Technology - A Review of the First International Meeting.pdf (0 bytes)
Brain-Computer Interface Technology - A Review of the First International Meeting.pdf (0 bytes)