Adaptive autoregressive parameters used in BCI research
An EEG-based BCI system is composed of different components including, an EEG recording, feature extraction and/or classification and online feedback. The system in Tübingen uses slow EEG potentials to control the feedback. In Albany, spectral parameters of the EEG are cumulated and used for on-line feedback. Since the beginning the Graz BCI system has been based on spectral analysis of the EEG in combination with some classifier (see Fig. 1). It is obvious that the subject’s ability to learn controlling his/her EEG patterns, does depend on the reliability of the feedback. One of the key components in a BCI system is the extraction of EEG features, best suitable to monitor the dynamics of different brain states.