Cargando…
A Bayesian Model for Exploiting Application Constraints to Enable Unsupervised Training of a P300-based BCI
This work introduces a novel classifier for a P300-based speller, which, contrary to common methods, can be trained entirely unsupervisedly using an Expectation Maximization approach, eliminating the need for costly dataset collection or tedious calibration sessions. We use publicly available datase...
| Autores principales: | , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2012
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3319551/ https://www.ncbi.nlm.nih.gov/pubmed/22496763 http://dx.doi.org/10.1371/journal.pone.0033758 |