PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The Berlin Brain-Computer Interface for Rapid Response
Matthias Krauledat, Guido Dornhege, Benjamin Blankertz, Gabriel Curio and Klaus-Robert Müller
Biomedizinische Technik (Biomedical Engineering) Volume 49, Number 1, pp. 61-62, 2004.

Abstract

The Berlin Brain-Computer Interface (BBCI) project is guided by the idea to train a computer using advanced machine learning and signal processing techniques in order to improve classification performance and to reduce the need of subject training. Instead of having the human adapt to a predefined feedback that is computed from a fixed set of features, the BBCI adapts to the user's brain waves by learning ('let the machines learn'). One aspect of the BBCI is the capability of giving fast-response feedback. This was investigated in keyboard typing paradigms with self-paced as well as reactive finger movements in a time critical task. In both settings a prediction of the laterality of upcoming movements was possible before EMG onset.

Postscript - Requires a viewer, such as GhostView
PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Article
Uncontrolled Keywords:Brain-Computer Interface, EEG single-trial analysis, lateralized readiness potential, signal processing, machine learning
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:10
Deposited By:Benjamin Blankertz
Deposited On:14 May 2004