Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach

@inproceedings{Krauledat2006ReducingCT,
  title={Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach},
  author={Matthias Krauledat and Michael Tangermann and Benjamin Blankertz and Klaus-Robert M{\"u}ller},
  booktitle={NIPS},
  year={2006}
}
Up to now even subjects that are experts in the use of machine learning based BCI systems still have to undergo a calibration session of about 20-30 min. From this data their (movement) intentions are so far infered. We now propose a new paradigm that allows to completely omit such calibration and instead transfer knowledge from prior sessions. To achieve this goal we first define normalized CSP features and distances in-between. Second, we derive prototypical features across sessions: (a) by… CONTINUE READING