Automatic Classification of Artifactual ICA-Components for Artifact Removal in EEG Signals

BACKGROUND: Artifacts contained in EEG recordings hamper both, the visual interpretation by experts as well as the algorithmic processing and analysis (e.g. for Brain-Computer Interfaces (BCI) or for Mental State Monitoring). While hand-optimized selection of source components derived from Independe...

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Detalles Bibliográficos
Autores principales: Winkler, Irene, Haufe, Stefan, Tangermann, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3175453/
https://www.ncbi.nlm.nih.gov/pubmed/21810266
http://dx.doi.org/10.1186/1744-9081-7-30

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3175453/
https://www.ncbi.nlm.nih.gov/pubmed/21810266
http://dx.doi.org/10.1186/1744-9081-7-30

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