Non-invasive brain-computer interfaces for semi-autonomous assistive devices

Abstract

A brain-computer interface (BCI) transforms brain activity into commands that can control computers and other technologies. Because brain signals recorded non-invasively from the scalp are difficult to interpret, robust signal processing methods have to be applied. Although state-of-the-art signal processing methods are used in BCI research, the output of a BCI is still unreliable, and the information transfer rates are very small compared with conventional human interaction interfaces. Therefore, BCI applications have to compensate for the unreliability and low information content of the BCI output. Controlling a wheelchair or a robotic arm would be slow, frustrating, or even dangerous if it solely relied on BCI output. Intelligent devices, however, such as a wheelchair that can automatically avoid collisions and dangerous situations or a service robot that can autonomously conduct goal-directed tasks and independently detect and resolve safety issues, are much more suitable for being controlled by an unreliable control signal like that provided by a BCI. © 2008 Springer-Verlag London.