title: Current trends in Graz Brain-Computer Interface (BCI) research.
abstract: 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.
authors.affiliation: Department of Medical Informatics, Institute for Biomedical Engineering, University of Technology Graz, Austria. pfu@dpmi.tu-graz.ac.at
authors.forename: G
authors.initials: G
authors.lastname: Pfurtscheller
authors.forename: C
authors.initials: C
authors.lastname: Neuper
authors.forename: C
authors.initials: C
authors.lastname: Guger
authors.forename: W
authors.initials: W
authors.lastname: Harkam
authors.forename: H
authors.initials: H
authors.lastname: Ramoser
authors.forename: A
authors.initials: A
authors.lastname: Schlögl
authors.forename: B
authors.initials: B
authors.lastname: Obermaier
authors.forename: M
authors.initials: M
authors.lastname: Pregenzer
mesh_terms: 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