Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain–computer interface: three-class classification of rest, right-, and left-hand motor execution

The aim of this work is to develop an effective brain–computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification...

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Detalles Bibliográficos
Autores principales: Trakoolwilaiwan, Thanawin, Behboodi, Bahareh, Lee, Jaeseok, Kim, Kyungsoo, Choi, Ji-Woong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2017
Materias:
Special Section on Functional Near Infrared Spectroscopy, Part 3
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5599227/
https://www.ncbi.nlm.nih.gov/pubmed/28924568
http://dx.doi.org/10.1117/1.NPh.5.1.011008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5599227/
https://www.ncbi.nlm.nih.gov/pubmed/28924568
http://dx.doi.org/10.1117/1.NPh.5.1.011008

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