@article{ref1,
title="Development of a neuroergonomic assessment for the evaluation of mental workload in an industrial human-robot interaction assembly task: a comparative case study",
journal="Machines (Basel)",
year="2023",
author="Caiazzo, Carlo and Savkovic, Marija and Pusica, Milos and Milojevic, Djordje and Leva, Maria Chiara and Djapan, Marko",
volume="11",
number="11",
pages="e995-e995",
abstract="The disruptive deployment of collaborative robots, named cobots, in Industry 5.0 has brought attention to the safety and ergonomic aspects of industrial human-robot interaction (HRI) tasks. In particular, the study of the operator's mental workload in HRI activities has been the research object of a new branch of ergonomics, called neuroergonomics, to improve the operator's wellbeing and the efficiency of the system. This study shows the development of a combinative assessment for the evaluation of mental workload in a comparative analysis of two assembly task scenarios, without and with robot interaction. The evaluation of mental workload is achieved through a combination of subjective (NASA TLX) and real-time objective measurements. This latter measurement is found using an innovative electroencephalogram (EEG) device and the characterization of the cognitive workload through the brainwave power ratio β/α, defined after the pre-processing phase of EEG data. Finally, observational analyses are considered regarding the task performance of the two scenarios. The statistical analyses show how significantly the mental workload diminution and a higher level of performance, as the number of components assembled correctly by the participants, are achieved in the scenario with the robot.<p /> <p>Language: en</p>",
language="en",
issn="2075-1702",
doi="10.3390/machines11110995",
url="http://dx.doi.org/10.3390/machines11110995"
}