Neuroergonomic Models and Tools Compared to Evaluate and Improve Human-Machine Interaction in Manufacturing

Industrialisation and the rapid progression in automation and digitalization have supported the common use of tools and machines in everyday life and workplaces, especially in industrial environments. The paper proposes a critical-analytical investigation aimed at fostering reflections on Human Factors and Neuroergonomics concepts and approaches to improve human-machine interactions in the workplace and with the support of Neuroimaging technologies and metrics used to track the cognitive state of the user-operator. The primary objective was to identify the industrial sectors most exposed to psychosocial risks, in order to prefigure specifically adapted and highly contextualized solutions. Particular attention was given to the integration of wearable and smart devices, designed to amplify operator safety and to accurately monitor the user’s psychophysical state. By exploring and analysing the state of the art of existing wearable and intelligent devices, critical factors, functionalities, performance, innovative architectures and technologies from different industries emerged. The results of this work have allowed critical factors and opportunities to emerge that are useful in designing and developing work environments that are safe, efficient and focused on the well-being of operators.