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Benjamin Blankertz

Researcher at Technical University of Berlin

Publications -  223
Citations -  23231

Benjamin Blankertz is an academic researcher from Technical University of Berlin. The author has contributed to research in topics: Brain–computer interface & Interface (computing). The author has an hindex of 65, co-authored 219 publications receiving 20706 citations. Previous affiliations of Benjamin Blankertz include Fraunhofer Society & Charité.

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Optimizing Spatial filters for Robust EEG Single-Trial Analysis

TL;DR: The theoretical background of the common spatial pattern (CSP) algorithm, a popular method in brain-computer interface (BCD research), is elucidated and tricks of the trade for achieving a powerful CSP performance are revealed.
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On the interpretation of weight vectors of linear models in multivariate neuroimaging.

TL;DR: It is demonstrated that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study, in contrast to the interpretation of backward model parameters.
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Single-Trial Analysis and Classification of ERP Components - a Tutorial

TL;DR: This tutorial proposes to use shrinkage estimators and shows that appropriate regularization of linear discriminant analysis (LDA) by shrinkage yields excellent results for single-trial ERP classification that are far superior to classical LDA classification.
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The non-invasive Berlin Brain-Computer Interface: fast acquisition of effective performance in untrained subjects.

TL;DR: It is proposed that the key to quick efficiency in the BBCI system is its flexibility due to complex but physiologically meaningful features and its adaptivity which respects the enormous inter-subject variability.
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The BCI competition III: validating alternative approaches to actual BCI problems

TL;DR: The third BCI Competition to address several of the most difficult and important analysis problems in BCI research is organized and the paper describes the data sets that were provided to the competitors and gives an overview of the results.