Digital Twin based on IoT and Ontology for remote physiotherapy

An aging population and unhealthy lifestyles have fueled an increase in high–risk metabolic conditions, particularly obesity and type–2 diabetes, posing significant public health challenges across Europe. Physical activity emerges as a cornerstone for improving motor performance and managing physiological/stress–related profiles in affected individuals. However, accessibility to preventive or adapted motor rehabilitation remains limited to specialized centers managed by healthcare professionals, leaving a substantial part of the population underserved. In response, we initiated a feasibility study towards an innovative framework, that aims to integrate real–time monitoring, motor training and rehabilitation supervision directly into the patient’s home environment. At the center of our approach is the concept of Digital Twin, which exploits IoT and edge computing technologies to remotely acquire and analyze physio–metabolic data. Through an ontology–based knowledge representation system, aligned with the healthcare professional’s perspective, this approach should enable personalized and proactive care delivery. By leveraging synergies between digital technology and healthcare expertise, our framework aims at giving patients greater autonomy over their health, while addressing the growing burden of metabolic disorders.