TY - GEN
T1 - The Berlin brain-computer interface
AU - Blankertz, Benjamin
AU - Tangermann, Michael
AU - Popescu, Florin
AU - Krauledat, Matthias
AU - Fazli, Siamac
AU - Dónaczy, Márton
AU - Curio, Gabriel
AU - Müller, Klaus Robert
PY - 2008/7/4
Y1 - 2008/7/4
N2 - The Berlin Brain-Computer Interface (BBCI) uses a machine learning approach to extract subject-specific patterns from high-dimensional EEG-features optimized for revealing the user's mental state. Classical BCI application are brain actuated tools for patients such as prostheses (see Section 4.1) or mental text entry systems ([2] and see [3,4,5,6] for an overview on BCI). In these applications the BBCI uses natural motor competences of the users and specifically tailored pattern recognition algorithms for detecting the user's intent. But beyond rehabilitation, there is a wide range of possible applications in which BCI technology is used to monitor other mental states, often even covert ones (see also [7] in the fMRI realm). While this field is still largely unexplored, two examples from our studies are exemplified in Section 4.3 and 4.4.
AB - The Berlin Brain-Computer Interface (BBCI) uses a machine learning approach to extract subject-specific patterns from high-dimensional EEG-features optimized for revealing the user's mental state. Classical BCI application are brain actuated tools for patients such as prostheses (see Section 4.1) or mental text entry systems ([2] and see [3,4,5,6] for an overview on BCI). In these applications the BBCI uses natural motor competences of the users and specifically tailored pattern recognition algorithms for detecting the user's intent. But beyond rehabilitation, there is a wide range of possible applications in which BCI technology is used to monitor other mental states, often even covert ones (see also [7] in the fMRI realm). While this field is still largely unexplored, two examples from our studies are exemplified in Section 4.3 and 4.4.
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U2 - 10.1007/978-3-540-68860-0_4
DO - 10.1007/978-3-540-68860-0_4
M3 - Conference contribution
AN - SCOPUS:46049085230
SN - 3540688587
SN - 9783540688587
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 79
EP - 101
BT - Computational Intelligence
T2 - 2008 IEEE World Congress on Computational Intelligence, WCCI 2008
Y2 - 1 June 2008 through 6 June 2008
ER -