A new methodology to evaluate Human Workload State Inference

Electronics and automation are increasingly part of our daily lives, and led to the introduction of systems and intelligent machines to which the human work is delegated and that collaborate and support the user in the conduct of mancritical operations. The University of Modena and Reggio Emilia is partner of the european project “Designing Dynamic Distributed Cooperative Human-Machine Systems” (D3CoS, www.d3cos.eu), that aim is the definition of affordable methods, techniques and tools which go beyond assistance systems and consequently address the specification, development and evaluation of cooperative systems from a multi-agent perspective where human and machine agents are in charge of common tasks, assigned to the system as a whole. The key on which to base the cooperation between the machine and the human is the amount of workload of the human operator. So we were involved into investigate aspects of the functional state of human operators interacting with the demonstrator in the unmanned aerial vehicle (UAV) and maritime domains. We analyzed and correlated objective psycho-physiological measures: eye blinks, respiration rate and amplitude, electro dermal activity, heart rate variability, blood pressure; with subjective self-assessed measure evaluated with two questionnaires: NASA-TLX and Rating Scale Mental Effort (RSME); with the aim to realize a mathematical regression model for classifying the mental operators workload. Keywords— Workload, psycho-physiological measures, statistical analysis, cooperative systems.