BCI Competitions

A Brain-Computer Interface (BCI) is a novel augmentative communication system that translates human intentions – reflected by suitable brain signals – into a control signal for an output device such as a computer application or a neuroprosthesis. In developing a BCI system many fields of research are involved, such as classification, signal processing, neurophysiology, measurement technology, psychology, control theory. In recent EEG-based BCI research the role of machine learning (a BCI approach pioneered by Fraunhofer FIRST at NIPS*01) becomes more and more important. In the literature, many machine learning and pattern classification algorithms have been reported to give impressive results when applied to BCI data in offline analyses. However, it is more difficult to evaluate their relative value for actual online use. Typically in each publication a different data set is used, such that — given the high inter-subject variability with respect to BCI performance — a comparison between different methods is practically impossible. Furthermore the offline evaluation EEG classification methods holds many possible pitfalls that lead to an overestimation of the performance. BCI data competitions have been organized to provide objective formal evaluations of alternative methods and therefore to foster the development of improved BCI technology by providing an unbiased validation of a variety of data analysis techniques.

Five Brain-Computer-Interface (BCI) competitions have been held, all to great success. The first BCI Competitions addressed basic problems of BCI research (most tasks posed the problem of classifying short term windows of defined mental states), and later BCI Competition addressed advanced problems with time-continuous feedback, classifiers that needed to be applied to sliding windows and the integration of different measurement sources for generating BCI control signals. More than 200 submissions from more than 50 different labs; one overview article has appeared (IEEE Trans Neural Sys Rehab Eng, 14(2):153-159, 2006) and a special volume of Lecture Notes Computational Science in 2010). Furthermore individual articles of the competition winners have appeared in different journals.