@inproceedings{6583,
  title = {Epidural ECoG Online Decoding of Arm Movement Intention in Hemiparesis},
  booktitle = {Proceedings of the 1st ICPR Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging (ICPR WBD 2010)},
  abstract = {Brain-Computer Interfaces (BCI) that rely upon epidural electrocorticographic signals may become a promising tool for neurorehabilitation of patients with severe hemiparatic syndromes due to cerebrovascular, traumatic or tumor-related brain damage. Here, we show in a patient-based feasibility study that online classification of arm movement intention is possible. The intention to move or to rest can be identified with high accuracy (~90 %), which is sufficient for BCI-guided neurorehabilitation. The observed spatial distribution of relevant features on the motor cortex indicates that cortical reorganization has been induced by the brain lesion. Low- and high-frequency components of the electrocorticographic power spectrum provide complementary information towards classification of arm movement intention.},
  pages = {36-39},
  editors = {J. Richiardi and D Van De Ville and C Davatzikos and J Mourao-Miranda},
  publisher = {IEEE},
  organization = {Max-Planck-Gesellschaft},
  institution = {Institute of Electrical and Electronics Engineers},
  school = {Biologische Kybernetik},
  address = {Piscataway, NJ, USA},
  month = aug,
  year = {2010},
  slug = {6583},
  author = {Gomez Rodriguez, M. and Grosse-Wentrup, M. and Peters, J. and Naros, G. and Hill, J. and Sch{\"o}lkopf, B. and Gharabaghi, A.},
  month_numeric = {8}
}