Determining Optimal Feature-Combination for LDA Classification of Functional Near-Infrared Spectroscopy Signals in Brain-Computer Interface Application

In this study, we determine the optimal feature-combination for classification of functional near-infrared spectroscopy (fNIRS) signals with the best accuracies for development of a two-class brain-computer interface (BCI). Using a multi-channel continuous-wave imaging system, mental arithmetic sign...

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Detalles Bibliográficos
Autores principales: Naseer, Noman, Noori, Farzan M., Qureshi, Nauman K., Hong, Keum-Shik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879140/
https://www.ncbi.nlm.nih.gov/pubmed/27252637
http://dx.doi.org/10.3389/fnhum.2016.00237

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879140/
https://www.ncbi.nlm.nih.gov/pubmed/27252637
http://dx.doi.org/10.3389/fnhum.2016.00237

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