The Berlin Brain-Computer Interface: Progress Beyond Communication and Control
- Authors
- Blankertz, Benjamin; Acqualagna, Laura; Dahne, Sven; Haufe, Stefan; -Kraft, Matthias Schultze; Sturm, Irene; Uscumlic, Marija; Wenzel, Markus A.; Curio, Gabriel; Muller, Klaus -Robert
- Issue Date
- 21-11월-2016
- Publisher
- FRONTIERS MEDIA SA
- Keywords
- Brain-Computer Interfacing (BCI); electroencephalography (EEG); covert user states; machine learning; mental workload; video quality; implicit information; cognitive neuroscience
- Citation
- FRONTIERS IN NEUROSCIENCE, v.10
- Indexed
- SCIE
SCOPUS
- Journal Title
- FRONTIERS IN NEUROSCIENCE
- Volume
- 10
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/86807
- DOI
- 10.3389/fnins.2016.00530
- ISSN
- 1662-4548
- Abstract
- The combined effect of fundamental results about neurocognitive processes and advancements in decoding mental states from ongoing brain signals has brought forth a whole range of potential neurotechnological applications. In this article, we review our developments in this area and put them into perspective. These examples cover a wide range of maturity levels with respect to their applicability. While we assume we are still a long way away from integrating Brain-Computer Interface (BCI) technology in general interaction with computers, or from implementing neurotechnological measures in safety-critical workplaces, results have already now been obtained involving a BCI as research tool. In this article, we discuss the reasons why, in some of the prospective application domains, considerable effort is still required to make the systems ready to deal with the full complexity of the real world.
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Collections - Graduate School > Department of Artificial Intelligence > 1. Journal Articles
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