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Abstract

This article presents the latest BCI-related research done in our group. Our previous work applied computational intelligence technology in BCIs to inspire detailed investigations of practical issues in real-life applications. Novel EEG devices featuring dry electrodes facilitate and speed up electrode positioning before recording and allow subjects to move freely in operational environments. We also demonstrate the feasibility of applying CCA, RBFNs, effective connectivity measurements, and D-S theory to help BCIs extract informative knowledge from brain signals. Two recent trends in research in the computational and artificial intelligence community, big data and deep learning, are expected to impact the direction and development of BCIs.

Item Type:	Article
Authors/Creators:	Lin, C-T and Liu, Y-T and Wu, S-L and Cao, Z and Wang, Y-K and Huang, C-S and King, J-T and Chen, S-A and Lu, S-W and Chuang, C-H
Keywords:	EEG, CI, brain-computer interfaces
Journal or Publication Title:	IEEE Systems, Man and Cybernetics Magazine
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	2333-942X
DOI / ID Number:	https://doi.org/10.1109/MSMC.2017.2702378
Copyright Information:	Copyright 2017 IEEE.
Related URLs:	Google Scholar: Cao, Z
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