Feature Extraction and Classification Methods for Hybrid fNIRS-EEG Brain-Computer Interfaces

Feature Extraction and Classification Methods for Hybrid fNIRS-EEG Brain-Computer Interfaces

In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) patients is investigated. Brain tasks, channel selection methods, and feature extraction and classification algorithms avai...

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Bibliographic Details
Main Authors: Keum-Shik Hong, M. Jawad Khan, Melissa J. Hong
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-06-01
Series:Frontiers in Human Neuroscience
Subjects:
brain-computer interface
electroencephalography
functional near-infrared spectroscopy
locked-in syndrome patient
feature extraction
classification
Online Access:https://www.frontiersin.org/article/10.3389/fnhum.2018.00246/full

Internet

https://www.frontiersin.org/article/10.3389/fnhum.2018.00246/full

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