One goal of medical device certification is to show that a given medical device satisfies its requirements. The requirements that should be met by a device, however, depend on the medical processes in which the device is to be used. Such processes may be complex and, thus, critical requirements may be specified inaccurately or incompletely, or even missed altogether. We are investigating a requirement derivation approach that takes as input a model of the way the device is used in a particular medical process and a requirement that should be satisfied by that process. This approach tries to produce a derived requirement for the medical device that is sufficient to prevent any violations of the process requirement. Our approach combines a method for generating assumptions for assume-guarantee reasoning with one for interface synthesis to automate the derivation of the medical device requirements. The proposed approach performs the requirement derivation iteratively by employing a model checker and a learning algorithm. We implemented this approach and evaluated it by applying it to two small case studies. Our experiences showed that the proposed approach could be successfully applied to abstract models of portions of real-world medical processes and that the derived requirements of the medical devices appeared useful and understandable.
Other work ( REF ) applies requirements analysis to identify new constraints that must be satisfied by the medical devices to avoid violations of the medical process.
Process-based derivation of requirements for medical devices
IHI
Computer Science