Advancing Neurodiversity Inclusivity for Operator 4.0: Cognitive Loads Modelling via Advanced Sensing Techniques

Neurodiversity can be an insurmountable barrier to carry out most of the tasks in the daily life. This thesis, through the use of robotics and sensor technology, aims to examine neurodiverse individuals in order to identify common traits, among the different neurodiversity types, to predict possible crises or human breakdowns that may arise while performing daily tasks. In this way, timely action can be taken to preserve the quality of the task a person is doing. At this purpose, the factors involved in the increase in the cognitive load have been studied and, in particular, to what extent these factors are stressed during the execution of ten specific tasks, identified as the main problems for industrial workers. Scientific literature and industrial practices have been reviewed to define the current state-of-the art in the field and the research gap. This thesis proposes a methodology to estimate relevant components of cognitive load. In this respect, physiological, breathing, eyes, behaviour, working environment and manufacturing data are processed using a fuzzy logic based approach.