Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an a...

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Detalles Bibliográficos
Autores principales: Zhang, Chi, Tong, Li, Zeng, Ying, Jiang, Jingfang, Bu, Haibing, Yan, Bin, Li, Jianxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4562337/
https://www.ncbi.nlm.nih.gov/pubmed/26380294
http://dx.doi.org/10.1155/2015/720450

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4562337/
https://www.ncbi.nlm.nih.gov/pubmed/26380294
http://dx.doi.org/10.1155/2015/720450

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