The Berlin brain-computer interface

Benjamin Blankertz, Michael Tangermann, Florin Popescu, Matthias Krauledat, Siamac Fazli, Márton Dónaczy, Gabriel Curio, Klaus Robert Müller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationComputational Intelligence
Subtitle of host publicationResearch Frontiers - IEEE World Congress on Computational Intelligence, WCCI 2008, Plenary/Invited Lectures
Number of pages23
Publication statusPublished - 2008
Event2008 IEEE World Congress on Computational Intelligence, WCCI 2008 - Hong Kong, Hong Kong
Duration: 2008 Jun 12008 Jun 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5050 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other2008 IEEE World Congress on Computational Intelligence, WCCI 2008
Country/TerritoryHong Kong
CityHong Kong

Bibliographical note

Copyright 2008 Elsevier B.V., All rights reserved.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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