Towards organ-centric compositional development of safe networked supervisory medical systems

Medical devices are increasingly capable of interacting with each other by leveraging network connectivity and interoperability, promising a great benefit for patient safety and effectiveness of medical services. However, ad-hoc integration of medical devices through networking can significantly increase the complexity of the system and make the system more vulnerable to potential errors and safety hazards. In this paper, we address this problem and introduce an organ-centric compositional development approach. In our approach, medical devices are composed into semi-autonomous clusters according to organ-specific physiology in a network-fail-safe manner. Each organ-centric cluster captures common device interaction patterns of sensing and control to support human physiology. The library of these formally verified organ-centric architectural patterns enables rapid and safe composition of supervisory controllers, which are specialized for specific medical scenarios. Using airway-laser surgery as a case study of practical importance, we demonstrate the feasibility of our approach under Simulink's model-driven development framework.