Zero training for BCI-reality for BCI systems based on event-related potentials

This contribution reviews how usability in Brain- Computer Interfaces (BCI) can be enhanced. As an ex- ample, an unsupervised signal processing approach is pre- sented, which tackles usability by an algorithmic improve- ment 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 ses- sion avoids the usual paradigmatic break between calibra- tion phase and online phase, which is known to introduce data-analytic problems related to non-stationarity