Research Topics
| A SchloglSummaryAffiliation: Graz University of Technology Country: Austria Publications
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Detail Information
Publications
Graz-BCI: state of the art and clinical applicationsG Pfurtscheller
Department of Medical Informatics, Institute of Biomedical Engineering, University of Technology Graz, 8010 Graz, Austria
IEEE Trans Neural Syst Rehabil Eng 11:177-80. 2003..Additionally, it is demonstrated how information transfer rates of 17 b/min can be acquired by real time classification of oscillatory activity...
A fully automated correction method of EOG artifacts in EEG recordingsA Schlogl
Institute of Human Computer Interfaces, Graz University of Technology, Krenngasse 37 IV, A 8010 Graz, Austria
Clin Neurophysiol 118:98-104. 2007..A fully automated method for reducing EOG artifacts is presented and validated...
Analyzing event-related EEG data with multivariate autoregressive parametersAlois Schlogl
Institute for Human Computer Interfaces, University of Technology at Graz, Graz, Austria
Prog Brain Res 159:135-47. 2006..Finally, we present several examples of coupling patterns associated with certain types of movement imagery...
Characterization of four-class motor imagery EEG data for the BCI-competition 2005Alois Schlogl
Institute of Human Computer Interfaces, University of Technology Graz, Krenngasse 37, A 8010 Graz, Austria
J Neural Eng 2:L14-22. 2005..Our results of the multi-channel analysis indicate SVM as the most successful classifier, whereas kNN performed worst...
15 years of BCI research at Graz University of Technology: current projectsG Pfurtscheller
Laboratory of Brain Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology, 8010 Graz, Austria
IEEE Trans Neural Syst Rehabil Eng 14:205-10. 2006..Recent projects deal with the development of asynchronous BCIs, the presentation of feedback and applications for communication and control...
Current trends in Graz Brain-Computer Interface (BCI) researchG Pfurtscheller
Department of Medical Informatics, Institute for Biomedical Engineering, University of Technology Graz, Austria
IEEE Trans Rehabil Eng 8:216-9. 2000..g. for cursor control. In a number of on-line experiments, various methods for EEG feature extraction and classification have been evaluated...
Rapid prototyping of an EEG-based brain-computer interface (BCI)C Guger
Institute for Biomedical Engineering, Department of Medical Informatics, University of Technology Graz, Austria
IEEE Trans Neural Syst Rehabil Eng 9:49-58. 2001..A classification accuracy between 70% and 95% could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive (AAR) model and linear discriminant analysis (LDA)...
Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasksG Pfurtscheller
Laboratory of Brain Computer Interfaces, Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16a, A 8010 Graz, Austria
Neuroimage 31:153-9. 2006..This implies that such EEG phenomena may be utilized in a multi-class brain-computer interface (BCI) operated simply by motor imagery...
Detection of movement-related desynchronization patterns in ongoing single-channel electrocorticogramBernhard Graimann
Department of Medical Informatics, Institute of Biomedical Engineering, University of Technology Graz, 8010 Graz, Austria
IEEE Trans Neural Syst Rehabil Eng 11:276-81. 2003....
Lexical memory search during N400: cortical couplings in auditory comprehensionGernot G Supp
Institute of Human Computer Interfaces, University of Technology, Inffeldgasse 16a, A 8010 Graz, Austria
Neuroreport 15:1209-13. 2004..Lexico-semantic memory search appears to be subserved by a network between temporal, parietal and frontal areas, particularly restricted to the left hemisphere...
Semantic memory retrieval: cortical couplings in object recognition in the N400 windowGernot G Supp
Institute of Human Computer Interfaces, University of Technology, Inffeldgasse 16a, A 8010 Graz, Austria
Eur J Neurosci 21:1139-43. 2005..Successful memory retrieval of picture meaning appears to be supported by networks comprising left temporal and parietal regions and bilateral frontal brain areas...
