The Berlin Brain-Computer Interface: machine learning allows direct
Since the 1970s some researcher and artists made experiments with neuro-feedback sys-tems that translated brain activity into some kind of visual, acoustic or tactile feedback. In the 80s the proof-of-concept was given that such Brain-Computer Interfaces (BCIs) can serve as communication tools for severely paralyzed patients. But during that time the operation of BCIs was fraught with several difﬁculties, the most critical being that the system worked only for few people and that even those had to practice the usage of the BCI system for a long time, typical several months. Nowadays data analysis algorithms are much more powerful entailing a boost in BCI research. This talk will provide an overview of current BCI research with a special focus on the work of the Berlin Brain-Computer Interface project.
Benjamin Blankertz received the Diploma degree in mathematics 1994 and the Ph.D. in mathematical logic in 1997, both from University of MÃ¼nster, Germany. He conducted studies in computational models for perception of music and computer-aided music analysis.
Since 2000 he is with the intelligent data analysis (IDA) group at Fraunhofer FIRST in Berlin working in the Berlin Brain-Computer Interface (BBCI) project. His scientiﬁc interests are in the ﬁelds of machine learning, analysis of biomedical data, and psychoacoustics.