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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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| Main Authors: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2014
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| Assuntos: | |
| Acesso em linha: | 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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