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The effects of automated artifact removal algorithms on electroencephalography-based Alzheimer's disease diagnosis

Over the last decade, electroencephalography (EEG) has emerged as a reliable tool for the diagnosis of cortical disorders such as Alzheimer's disease (AD). EEG signals, however, are susceptible to several artifacts, such as ocular, muscular, movement, and environmental. To overcome this limitat...

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Hlavní autoři: Cassani, Raymundo, Falk, Tiago H., Fraga, Francisco J., Kanda, Paulo A. M., Anghinah, Renato
Médium: Artigo
Jazyk:Inglês
Vydáno: Frontiers Media S.A. 2014
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC3971195/
https://ncbi.nlm.nih.gov/pubmed/24723886
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnagi.2014.00055
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