Current trends in Graz Brain-Computer Interface (BCI) research.
This paper describes a research approach to develop a brain-computer interface (BCI) based on recognition of subject-specific EEG patterns. EEG signals recorded from sensorimotor areas during mental imagination of specific movements are classified on-line and used e.g. for cursor control. In a number of on-line experiments, various methods for EEG feature extraction and classification have been evaluated.
Pfurtscheller
G
G
Department of Medical Informatics, Institute for Biomedical Engineering, University of Technology Graz, Austria. pfu@dpmi.tu-graz.ac.at
Neuper
C
C
Guger
C
C
Harkam
W
W
Ramoser
H
H
Schlögl
A
A
Obermaier
B
B
Pregenzer
M
M
D000513:Alpha Rhythm; D001676:Biofeedback, Psychology / Q000502:physiology; D003143:Communication Devices for People with Disabilities; D004569:Electroencephalography / Q000295:instrumentation*; D006801:Humans; D007092:Imagination / Q000502:physiology*; D009044:Motor Cortex / Q000502:physiology*; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D013003:Somatosensory Cortex / Q000503:physiopathology; D014584:User-Computer Interface