A Risk-driven Methodology in Developing Ambient Intelligence Healthcare Systems

Ambient Intelligence Healthcare Systems (AmI-HSs) are increasingly being deployed in hospitals, nursing homes, medical environment with the aim of supporting physicians to manage the complexity of performing varied medical activities. Such systems have to be able to handle multiple medical devices, and human activities in a dynamic environment in which people and things can evolve over time as well as change their position with respect to the operational ambient. Design reliable AmI-HSs is of great importance since such system are considered safety-critical, but no software development life cycle (SDLC) exists that supports a design for reliability approach suited for AmI-HS, which must abide by international regulations to guarantee safety and effectiveness. To fill this gap, in this work a evidence-oriented, risk-driven design methodology is proposed. The novelty of our approach consists of interleaving risk management activities within the SDLC, and by guiding the design using evidence produced via a probabilistic risk assessment approach.