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Dynamic filtering improves attentional state prediction with fNIRS
Brain activity can predict a person’s level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise – thereby increasing such state prediction accuracy – rem...
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| Publicado no: | Biomed Opt Express |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Optical Society of America
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4866469/ https://ncbi.nlm.nih.gov/pubmed/27231602 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1364/BOE.7.000979 |
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