Proceedings of the

The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK

Framework of a Neuroergonomic Assessment in Human-Robot Collaboration

Carlo Caiazzo1,a, Marija Savković1,b, Miloš Pušica2, Nastasija Nikolic1,c, Djordje Milojevic1,d and Marko Djapan1,e

1Faculty of Engineering, University of Kragujevac, Serbia.

2mBrainTrain D.o.o., Belgrade, Serbia.


Human-robot Collaboration (HRC) is a relevant research field dealing with socio-technical and economic issues to consider in manufacturing industries. A Human-robot team, where the partners are human and robot, committed to reach a common goal through a collaboration, is the highest grade of interaction according to the different modes of integration of the robot in the manufacturing workplaces. In this regard, collaborative robots, or cobots, have enthusiastically found application in manufacturing assembly activities. However, the implementation of the cobot in the manufacturing workplace might be challenging as it requires a changeover of the environment, and it might be critically decided according to the task defined. Despite these drawbacks, the benefits highlighted by previous research works seem positively impact on the physical and mental health of the operator working alongside these machines. This research paper shows the impact of cobots on operators and the surrounding work environment from a neuroergonomic point of view. The article proposes a comparative analysis in a laboratory workstation set up for manufacturing assembly tasks, in which the operator accomplish an assembly task with and without the robot assistance. The presence of the robot is the element of comparison in the experimental design of the assembly task. The paper presents a comparative evaluation of the mental workload of the operator performing the task with and without the machine. The collection and analysis of physiological data, through electroencephalogram (EEG) devices, extend the possibility to set an ergonomic evaluation of the cognitive state of the operator during the HRC application.

Keywords: Human-robot collaboration, Neuroergonomics, Collaborative robotics, Mental workload, I4.0, EEG.

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