A Bibliometric Analysis of EEG Based Mental Workload Assessment Research

Weilin Chen and Zhikun Ding ()
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Weilin Chen: Shenzhen University
Zhikun Ding: Shenzhen University

A chapter in Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate, 2021, pp 219-233 from Springer

Abstract: Abstract This paper aims to provide a critical review of the recent literature for mental fatigue studies using Electroencephalogram (EEG) sensor. Mental fatigue could cause many failures and dangers in workplaces. To prevent adverse effects on performance and safety, many physiological sensors are used to detect metal fatigue, especially EEG sensor. To analyze the research frontiers, 519 related articles published between 2010 and 2019 were retrieved from the Web of Science. With text mining and Latent Dirichlet Allocation (LDA) topic modeling, the number of published papers, major research countries and institutions, primary research topics and their contents were examined and discussed. It is found that with the increasing importance of work safety and technological progress, EEG based mental fatigue research has gradually become a hot research field, and many inter-discipline studies have emerged, for example, in the field of construction and education. This study provides a knowledge map of current EEG based research and suggests potential interdisciplinary studies for future research, especially in the construction industry.

Keywords: EEG; Mental fatigue; LDA; Text mining; Bibliometric analysis (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-16-3587-8_16

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DOI: 10.1007/978-981-16-3587-8_16

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