Zero Training for BCI – Reality for BCI Systems Based on Event-Related Potentials

Abstract

This contribution reviews how usability in BrainComputer Interfaces (BCI) can be enhanced. As an example, an unsupervised signal processing approach is presented, which tackles usability by an algorithmic improvement from the field of machine learning. The approach completely omits the necessity of a calibration recording for BCIs based on event-related potential (ERP) paradigms. The positive effect is twofold -first, the experimental time is shortened and the productive online use of the BCI system starts as early as possible. Second, the unsupervised session avoids the usual paradigmatic break between calibration phase and online phase, which is known to introduce data-analytic problems related to non-stationarity.