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EEG-based brain-computer interfaces (BCIs): a survey of recent studies on signal sensing technologies and computational intelligence approaches and their applications

Citation

Gu, X and Cao, Z and Jolfaei, A and Xu, P and Wu, D and Jung, TP and Lin, CT, EEG-based brain-computer interfaces (BCIs): a survey of recent studies on signal sensing technologies and computational intelligence approaches and their applications, IEEE/ACM Transactions on Computational Biology and Bioinformatics ISSN 1545-5963 (2021) [Refereed Article]

Copyright Statement

2021 IEEE.

DOI: doi:10.1109/TCBB.2021.3052811

Abstract

IEEE Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact with the environment. Recent advancements in technology and machine learning algorithms have increased interest in electroencephalographic (EEG)-based BCI applications. EEG-based intelligent BCI systems can facilitate continuous monitoring of fluctuations in human cognitive states under monotonous tasks, which is both beneficial for people in need of healthcare support and general researchers in different domain areas. In this review, we survey the recent literature on EEG signal sensing technologies and computational intelligence approaches in BCI applications, compensating for the gaps in the systematic summary of the past five years. Specifically, we first review the current status of BCI and signal sensing technologies for collecting reliable EEG signals. Then, we demonstrate state-of-the-art computational intelligence techniques, including fuzzy models and transfer learning in machine learning and deep learning algorithms, to detect, monitor, and maintain human cognitive states and task performance in prevalent applications. Finally, we present a couple of innovative BCI-inspired healthcare applications and discuss future research directions in EEG-based BCI research.

Item Details

Item Type:Refereed Article
Keywords:electroencephalography, brain, deep learning, sensors, monitoring, functional magnetic resonance imaging, entertainment industry, EEG, BCI, AI
Research Division:Information and Computing Sciences
Research Group:Human-centred computing
Research Field:Human-computer interaction
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Applied computing
UTAS Author:Gu, X ( Xiaotong Gu)
UTAS Author:Cao, Z (Dr Zehong Cao)
ID Code:142425
Year Published:2021
Web of Science® Times Cited:8
Deposited By:Information and Communication Technology
Deposited On:2021-01-16
Last Modified:2021-11-23
Downloads:0

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