eCite Digital Repository

EEG-based brain-computer interfaces: a novel neurotechnology and computational intelligence method

Citation

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, EEG-based brain-computer interfaces: a novel neurotechnology and computational intelligence method, IEEE Systems, Man and Cybernetics Magazine, 3, (4) pp. 16-26. ISSN 2333-942X (2017) [Refereed Article]

Copyright Statement

Copyright 2017 IEEE.

DOI: doi:10.1109/MSMC.2017.2702378

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 Details

Item Type:Refereed Article
Keywords:EEG, CI, brain-computer interfaces
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Expert Systems
Objective Division:Defence
Objective Group:Defence
Objective Field:Intelligence
UTAS Author:Cao, Z (Mr Zehong Cao)
ID Code:131543
Year Published:2017
Web of Science® Times Cited:10
Deposited By:Information and Communication Technology
Deposited On:2019-03-21
Last Modified:2019-05-13
Downloads:0

Repository Staff Only: item control page