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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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Publicado no: | Biomed Res Int |
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Main Authors: | , , , , , , |
Formato: | Artigo |
Idioma: | Inglês |
Publicado em: |
Hindawi Publishing Corporation
2015
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Assuntos: | |
Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4562337/ https://ncbi.nlm.nih.gov/pubmed/26380294 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2015/720450 |
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