Empirische Inferenz Article 2010

A generative model approach for decoding in the visual event-related potential-based brain-computer interface speller

There is a strong tendency towards discriminative approaches in brain-computer interface (BCI) research. We argue that generative model-based approaches are worth pursuing and propose a simple generative model for the visual ERP-based BCI speller which incorporates prior knowledge about the brain signals. We show that the proposed generative method needs less training data to reach a given letter prediction performance than the state of the art discriminative approaches.

Author(s): Martens, SMM. and Leiva, JM.
Journal: Journal of Neural Engineering
Volume: 7
Number (issue): 2
Pages: 1-10
Year: 2010
Month: April
Day: 0
Bibtex Type: Article (article)
DOI: 10.1088/1741-2560/7/2/026003
Digital: 0
Electronic Archiving: grant_archive
EPUB: 026003
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex

@article{6262,
  title = {A generative model approach for decoding in the visual event-related potential-based brain-computer interface speller},
  journal = {Journal of Neural Engineering},
  abstract = {There is a strong tendency towards discriminative approaches in brain-computer interface (BCI) research. We argue that generative model-based approaches are worth pursuing and propose a simple generative model for the visual ERP-based BCI speller which incorporates prior knowledge about the brain signals. We show that the proposed generative method needs less training data to reach a given letter prediction performance than the state of the art discriminative approaches.},
  volume = {7},
  number = {2},
  pages = {1-10},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = apr,
  year = {2010},
  slug = {6262},
  author = {Martens, SMM. and Leiva, JM.},
  month_numeric = {4}
}