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Danger, high voltage! Using EEG and EOG measurements for cognitive overload detection in a simulated industrial context.
Tijdschriftbijdrage - Tijdschriftartikel
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.
Tijdschrift: Applied Ergonomics
ISSN: 0003-6870
Volume: 102
Pagina's: 1 - 9
Jaar van publicatie:2022
Toegankelijkheid:Open