Titlebook: Brain-Computer Interface Research; A State-of-the-Art S Christoph Guger,Gernot Müller-Putz,Brendan Allison Book 2015 The Author(s) 2015 201

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https://doi.org/10.1007/978-3-662-50329-4orithm that uses a Bayesian approach to collect only the amount of data necessary to reach a specified confidence level in the BCI’s decision based on continuous evaluation of the quality of a user’s responses. We further optimized the algorithm by incorporating statistical information about the use

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https://doi.org/10.1007/978-3-663-00202-4d to classify the presented image. When applied to continuously recorded brain activity, our decoding technique could accurately predict whether each stimulus was a face, house, or neither, with ~20 ms timing error. These results provide a roadmap for improved brain-computer interfacing tools to hel

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