Help Privacy Policy Disclaimer
  Advanced SearchBrowse




Conference Paper

EEG Source Localization for Brain-Computer-Interfaces

There are no MPG-Authors in the publication available
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available

Grosse-Wentrup, M., Gramann, K., Wascher, E., & Buss, M. (2005). EEG Source Localization for Brain-Computer-Interfaces. In 2nd International IEEE EMBS Conference on Neural Engineering, 2005 (pp. 128-131). Piscataway, NJ, USA: IEEE.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-D5F7-0
While most EEG based brain-computer-interfaces (BCIs) employ machine learning algorithms for classification, we propose to utilize source localization procedures for this purpose. Although the computational demand is considerably higher, this approach could allow the simultaneous classification of a multitude of conditions. We present an extension of independent component analysis (ICA) - based source localization that is fully automatic, and apply this method to the classification of EEG data generated by imaginary movements of the right and left index finger. The results demonstrate that source localization provides a viable alternative to machine learning algorithms for BCIs.