Mathematical Model and AI Oriented Analysis for Self-Regulated Learning in Remote Health Treatments

The paper aims to develop a new technological solution to support Self-Regulated Learning (SRL) of patients, thus to optimize benefits of the action plan for remote health treatments. We investigate an innovative Mathematical Model (MM) in the area of SRL to exhaustively describe the main aspects concerning the nature of human thought and cognition. Internet of Mobile Things (IoMT) adopted in remote Healthcare Systems (RHS) can improve self-learning capabilities of patients. However, the impact of technologies in remote therapies depends on several factors, such as technical skill levels of patients and the type of target to reach. The proposed MM is the basis for a post-processing performed with Machine Learning tools useful to identify cross-relations among key factors in SRL, such as digital skills, personal motivations of patients and therapy targets, and to investigate the impact of technological tools in RHS where technologies are used to training SRL.