Neurophysiological Predictor of SMR-Based BCI Performance

Brain-Computer Interfaces (BCIs) allow a user to control a computer appli-cation by brain activity as measured, e.g., by electroencephalography (EEG). After about 30 years of BCI research, the success of control that is achieved by means of a BCI system still greatly varies between subjects. For about 20% of potential users the obtained accuracy does not reach the level criterion, meaning that BCI control is not accurate enough to control an application. The determination of factors that may serve to predict BCI performance, and the development of methods to quantify a predictor value from psychological and/or physiological data serves two purposes: a better understanding of the ‘BCI-illiteracy phenomenon’, and avoidance of a costly and eventuall