Engineering of Trust Analysis-Driven Digital Twins for a Medical Device

The DT paradigm has emerged as a suitable way to cope with the complexity of analyzing, controlling, and adapting complex systems in diverse domains. For medical systems, however, the DT paradigm is not fully exploited mainly due to the complexity of dealing with uncertain human behavior, and of preventing sensitive information leakage (e.g., patient personal medical profiles). We present the first results of a long-term recently launched research aiming at engineering a DT for a medical device endowed with trust analyses techniques able to deal with human and environmental uncertainty, and security protection. As a proof of concept, we apply our DT vision to the case study of a mechanical ventilator developed for Covid 19 patient care. The long-term aim is engineering a new generation of lung ventilators where the use of a DT can prevent unreliability and untrustworthiness of a system where interactions, both physical (machine-patient) and operational (machine-medical staff), are characterized by the presence of uncertainty and vulnerabilities.