The aim of this paper is to show that machine learning techniques can be used to derive a classifying function for human brain signal data measured by magnetoencephalography (MEG)...
We outline the Berlin Brain-Computer Interface (BBCI), a system which enables us to translate brain signals from movements or movement intentions into control commands. The main co...
Benjamin Blankertz, Guido Dornhege, Steven Lemm, M...
In this paper we investigate the classification of mental tasks based on electroencephalographic (EEG) data for Brain Computer Interfaces (BCI) in two scenarios: off line and on-l...
Abstract. We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can “mind-type” text on a computer screen. The application is based on detectin...
Nikolay Chumerin, Nikolay V. Manyakov, Adrien Comb...
Moving a brain-computer interface from a laboratory demonstration to real-life applications poses severe challenges to the BCI community. Recently, with advances in the biomedical ...