The pandemic has accelerated the use of medical devices integrated with telemedicine technology in clinical processes. Companies are expanding the functionalities of their basic products by developing AI-based applications to deal with the increased amount of available data for both medical staff and patients. The translation of keywords like patient empowerment, digital twins, and clinical decision aid systems from research to products is becoming a reality.

The applications are for elderly or fragile people that need a continuous monitoring of the evolution of their pathologies for an early detection of changes that can lead to a worsening of the patient’s clinical status. Through the use of telemedicine platforms for telemonitoring it is possible to acquire physiological signals from different sensors and data entered by the patients or their caregivers. The natural evolution of this type of product is to integrate them with intelligent systems able to extract information from the data.

The research focuses on the development of a digital twin that, associated with a telemedicine platform, will be able to support patients that are inserted in a home care clinical pathway, caregivers, and medical staff. In particular, the goals are to develop a system that: a) analyzes the collected data daily and generates different kinds of alarms if it detects changes in the patient’s clinical status; b) summarizes the data to produce information for specialist visits; c) allows the patient and/or the caregiver to actively interact with the medical staff; d) allows the medical team (general practitioner, specialists, home care nurses, etc…) to share information.


  • Andrea Scotto (Ph.D. Student)
  • Samanta Rosati (Assistant Professor with time contract (RTD/b))
  • Gabriella Balestra (Confirmed Assistant Professor)