Publication
Title
Danger, high voltage! Using EEG and EOG measurements for cognitive overload detection in a simulated industrial context
Author
Abstract
Industrial settings will be characterized by far-reaching production automation brought about by advancements in robotics and artificial intelligence. As a consequence, human assembly workers will need to adapt quickly to new and more complex assembly procedures, which are most likely to increase cognitive workload, or potentially induce overload. Measurement and optimization protocols need to be developed in order to be able to monitor workers' cognitive load. Previous studies have used electroencephalographic (EEG, measuring brain activity) and electrooculographic (EOG, measuring eye movements) signals, using basic computer-based static tasks and without creating an experience of overload. In this study, EEG and EOG data was collected of 46 participants performing an ecologically valid assembly task while inducing three levels of cognitive load (low, high and overload). The lower individual alpha frequency (IAF) was identified as a promising marker for discriminating between different levels of cognitive load and overload.
Language
English
Source (journal)
Applied ergonomics : human factors in technology and society. - Guildford, 1969, currens
Publication
Guildford : 2022
ISSN
0003-6870 [print]
1872-9126 [online]
DOI
10.1016/J.APERGO.2022.103763
Volume/pages
102 (2022) , 9 p.
Article Reference
103763
ISI
000799853100004
Pubmed ID
35405457
Medium
E-only publicatie
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Publication type
Subject
External links
Web of Science
Record
Identifier
Creation 13.11.2023
Last edited 25.04.2024
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