Dottorato in MORFOGENESI E INGEGNERIA TISSUTALE

Titolo della tesi: Measuring mental workload, stress, and emotional state in working places: theory and applications

Both in research and industry domains the mental and emotional states’ monitoring is becoming relevantly important. Starting from few decades ago, there was a shift in the focus from workers’ physical demands to their cognitive demands. This shift is particularly evident in the context of elderly workers, who are required to deal with constantly evolving technologies, loss of knowledge, and potential poor healthy working conditions. Furthermore, the teleworking spread on global scale following the COVID-19 pandemic led to furtherly increase the need of objective methodologies to monitor the workers’ mental states, such as the mental workload, stress, and emotional status.My research activity aimed to develop methodologies able to evaluate, even online, the user’s mental workload, stress, and emotional state based on his/her brain and autonomic activities measured by Electroencephalography, Electrodermal Activity, and Photoplethysmography, in operational environments, facing all the issues related to perform reliable neurophysiological measures outside the laboratory-controlled conditions. In addition, an innovative video-based methodology was developed to remotely evaluate the workers’ mental and emotional states. A first experimental phase assessed the reliability of the considered wearable devices with the respect to the laboratory equipment and the accuracy of the video-based methodology in a controlled environment. A second experimental phase corresponded to the application of the developed methodologies in three real working environments. The developed methodologies were successfully validated in controlled and industrial environments, i.e., teleworking, manufacturing, office, and car driving environments on real workers. In particular, the developed methods allowed to evaluate the workers’ mental and emotional states positively and significantly correlated (all r > 0.68; all p < 0.05) with the respect to the measurements derived by the laboratory equipment and the subjective assessments. Finally, such methodologies were interfaced with a reasoning platform able to provide online suggestions and advice to the workers, in order to improve their wellbeing inside and outside their working environment. The overall results of my PhD research activity are satisfying and very promising. The main objective of my project was achieved through the development of different methodologies to objectively evaluate the workers’ mental workload, stress, and emotional state in real working environments by measuring their brain and autonomic activities. Furthermore, such methodologies were already integrated in a reasoning and assistive tool to support the workers and improve their wellbeing, which was successfully tested among real workers in three different European companies in the context of the Horizon 2020 WorkingAge Research Project.