Application of artificial intelligence techniques for brain-computer interface in mental fatigue detection: a systematic review (2011-2022)

Yaacob, Hamwira Sakti and Hossain, farhad and Shari, Sharunizam and Khare, Smith K. and Ooi, Chui Ping and Acharya, Rajendra Udyavara (2023) Application of artificial intelligence techniques for brain-computer interface in mental fatigue detection: a systematic review (2011-2022). IEEE Access, 11. pp. 74736-74758. E-ISSN 2169-3536

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Abstract

Mental fatigue is a psychophysical condition with a significant adverse effect on daily life, compromising both physical and mental wellness. We are experiencing challenges in this fast-changing environment, and mental fatigue problems are becoming more prominent. This demands an urgent need to explore an effective and accurate automated system for timely mental fatigue detection. Therefore, we present a systematic review of brain-computer interface (BCI) studies for mental fatigue detection using artificial intelligent (AI) techniques published in Scopus, IEEE Explore, PubMed and Web of Science (WOS) between 2011 and 2022. The Boolean search expression that comprised (((ELECTROENCEPHALOGRAM) AND (BCI)) AND (FATIGUE CLASSIFICATION)) AND (BRAIN-COMPUTER INTERFACE) has been used to select the articles. Through the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) methodology, we selected 39 out of 562 articles. Our review identified the research gap in employing BCI for mental fatigue intervention through automated neurofeedback. The AI techniques employed to develop EEG-based mental fatigue detection are discussed. We have presented comprehensive challenges and future recommendations from the gaps identified in discussions. The future direction includes data fusion, hybrid classification models, availability of public datasets, uncertainty, explainability, and hardware implementation strategies.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Brain-Computer Interface (BCI), electroencephalogram (EEG), mental fatigue detection, PRISMA
Subjects:	T Technology > T Technology (General) > T55.4 Industrial engineering.Management engineering. > T58.5 Information technology
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Dr Hamwira Yaacob
Date Deposited:	15 Aug 2023 14:49
Last Modified:	28 Aug 2023 17:52
URI:	http://irep.iium.edu.my/id/eprint/105635

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