User State Estimation Methods For Tailoring Human-Robot Interaction

The study of the interaction between humans and technology is paramount to designing customized devices that can improve interaction quality and effectiveness. Tailored systems have three main components: a Monitoring System that collects information on the user's health condition, a User State Estimation Module that extracts a synthetic indication of the person's status from monitored data, and an Interaction Manager Module that performs actions and provides feedback to the user. Tailored devices can be applied in various operational scenarios, such as improving the quality of human-robot interaction in robot-aided rehabilitation and improving worker health and safety in smart workplaces. The objective of this thesis work is to introduce novel approaches to accurately assess the physical and cognitive state of users and adjust the interaction between the users and technological solutions accordingly. The outputs of the research carried out in this thesis had an impact on robot-aided rehabilitation and the improvement of workers' health and safety. The tailoring of the robotic treatment will enhance the learned motor skills and the quality of human-robot interaction in the context of robot-assisted rehabilitation. The proposed methods will focus on delivering highly specific and individualized treatments to users that fit their particular status and health condition. Moreover, similar paradigms can be exploited in workplaces. The workers monitoring through wearable technologies enables the prevention of work-related injuries and illnesses. Robotic solutions such as collaborative robots, exoskeletons, and service robots can be used to improve worker health and safety conditions.