Suppression of overlearning in independent component analysis used for removal of muscular artifacts from electroencephalographic records

This paper addresses the overlearning problem in the independent component analysis (ICA) used for the removal of muscular artifacts from electroencephalographic (EEG) records. We note that for short EEG records with high number of channels the ICA fails to separate artifact-free EEG and muscular ar...

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Detalles Bibliográficos
Autores principales: Sebek, Jan, Bortel, Radoslav, Sovka, Pavel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091961/
https://www.ncbi.nlm.nih.gov/pubmed/30106969
http://dx.doi.org/10.1371/journal.pone.0201900

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091961/
https://www.ncbi.nlm.nih.gov/pubmed/30106969
http://dx.doi.org/10.1371/journal.pone.0201900

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