title: Toward smarter BCIs: extending BCIs through hybridization and intelligent control.
abstract: This paper summarizes two novel ways to extend brain-computer interface (BCI) systems. One way involves hybrid BCIs. A hybrid BCI is a system that combines a BCI with another device to help people send information. Different types of hybrid BCIs are discussed, along with challenges and issues. BCIs are also being extended through intelligent systems. Software that allows high-level control, incorporates context and the environment and/or uses virtual reality can substantially improve BCI systems. Throughout the paper, we critically address the real benefits of these improvements relative to existing technology and practices. We also present new challenges that are likely to emerge as these novel BCI directions become more widespread.
authors.affiliation: Institute for Knowledge Discovery, Graz University of Technology, Graz, Austria. allison@tugraz.at
authors.forename: B Z
authors.initials: BZ
authors.lastname: Allison
authors.forename: R
authors.initials: R
authors.lastname: Leeb
authors.forename: C
authors.initials: C
authors.lastname: Brunner
authors.forename: G R
authors.initials: GR
authors.lastname: Müller-Putz
authors.forename: G
authors.initials: G
authors.lastname: Bauernfeind
authors.forename: J W
authors.initials: JW
authors.lastname: Kelly
authors.forename: C
authors.initials: C
authors.lastname: Neuper
mesh_terms: D001185:Artificial Intelligence; D001676:Biofeedback, Psychology / Q000379:methods / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D025461:Feedback, Physiological / Q000502:physiology; D006801:Humans; D014584:User-Computer Interface