EEG-Based Brain-Computer Interfaces: A Novel Neurotechnology and Computational Intelligence Method

Lin, C; Liu, Y-T; Wu, S-L; Cao, Z; Wang, Y; Huang, C-S; King, J-T; Chen, S-A; Lu, S-W; Chuang, C

EEG-Based Brain-Computer Interfaces: A Novel Neurotechnology and Computational Intelligence Method

Lin, C

Liu, Y-T

Wu, S-L Cao, Z

Wang, Y

Huang, C-S King, J-T Chen, S-A Lu, S-W Chuang, C

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Systems Man and Cybernetics Magazine, 2017, 3 (4), pp. 16 - 26
Issue Date:: 2017-10-12

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Field	Value	Language
dc.contributor.author	Lin, C https://orcid.org/0000-0001-8371-8197	en_US
dc.contributor.author	Liu, Y-T https://orcid.org/0000-0001-6184-2373	en_US
dc.contributor.author	Wu, S-L	en_US
dc.contributor.author	Cao, Z https://orcid.org/0000-0003-3656-0328	en_US
dc.contributor.author	Wang, Y https://orcid.org/0000-0001-8390-2664	en_US
dc.contributor.author	Huang, C-S	en_US
dc.contributor.author	King, J-T	en_US
dc.contributor.author	Chen, S-A	en_US
dc.contributor.author	Lu, S-W	en_US
dc.contributor.author	Chuang, C https://orcid.org/0000-0002-5043-8380	en_US
dc.date.issued	2017-10-12	en_US
dc.identifier.citation	IEEE Systems Man and Cybernetics Magazine, 2017, 3 (4), pp. 16 - 26	en_US
dc.identifier.issn	2333-942X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/124416
dc.description.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.	en_US
dc.publisher	Institute of Electrical and Electronics Engineers	en_US
dc.relation.ispartof	IEEE Systems Man and Cybernetics Magazine	en_US
dc.relation.isbasedon	10.1109/MSMC.2017.2702378	en_US
dc.title	EEG-Based Brain-Computer Interfaces: A Novel Neurotechnology and Computational Intelligence Method	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	3	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0903 Biomedical Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	open_access
pubs.consider-herdc	false	en_US
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	3	en_US

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.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/124416