Enhancing Performance of a Hybrid EEG-fNIRS System Using Channel Selection and Early Temporal Features

Brain-Computer Interface (BCI) techniques hold a great promise for neuroprosthetic applications. A desirable BCI system should be portable, minimally invasive, and feature high classification accuracy and efficiency. As two commonly used non-invasive brain imaging modalities, Electroencephalography...

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Detalles Bibliográficos
Autores principales: Li, Rihui, Potter, Thomas, Huang, Weitian, Zhang, Yingchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5605645/
https://www.ncbi.nlm.nih.gov/pubmed/28966581
http://dx.doi.org/10.3389/fnhum.2017.00462

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5605645/
https://www.ncbi.nlm.nih.gov/pubmed/28966581
http://dx.doi.org/10.3389/fnhum.2017.00462

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