A model-driven design and validation of closed-loop medical device systems is presented. Currently, few if any medical systems on the market support closed-loop control of interconnected medical devices, and mechanisms for regulatory approval of such systems are lacking. We present a system implementing a clinical scenario where closed-loop control may reduce the possibility of human error and improve safety of the patient. The safety of the system is studied with a simple controller proposed in the literature. We demonstrate that, under certain failure conditions, safety of the patient is not guaranteed. Finally, a more complex controller is described and ensures safety even when failures are possible. This investigation is an early attempt to introduce automatic control in clinical scenarios and to delineate a methodology to validate such patient-inthe-loop systems for safe and correct operation. Comments
In modern hospitals, patients are treated using a wide array of medical devices that are increasingly interacting with each other over the network, thus offering a perfect example of a cyber-physical system. We study the safety of a medical device system for the physiologic closed-loop control of drug infusion. The main contribution of the paper is the verification approach for the safety properties of closed-loop medical device systems. We demonstrate, using a case study, that the approach can be applied to a system of clinical importance. Our method combines simulation-based analysis of a detailed model of the system that contains continuous patient dynamics with model checking of a more abstract timed automata model. We show that the relationship between the two models preserves the crucial aspect of the timing behavior that ensures the conservativeness of the safety analysis. We also describe system design that can provide open-loop safety under network failure.
As software becomes ever more ubiquitous and complex in medical devices, it becomes increasingly important to assure that it performs safely and effectively. The critical nature of medical devices necessitates that the software used therein be reliable and free of errors. It becomes imperative, therefore, to have a conformance review process in place to ascertain the correctness of the software and to ensure that it meets all requirements and standards.Formal methods have long been suggested as a means to design and develop medical device software. However, most manufacturers shy from using these techniques, citing them as too complex and time consuming. As a result, (potentially life-threatening) errors are often not discovered until a device is already on the market.In this paper we present a safety model based approach to software conformance checking. Safety models enable the application of formal methods to software conformance checking, and provide a framework for rigorous testing. To illustrate the approach, we develop the safety model for a Generic Infusion Pump (GIP), and explain how it can be used to aid software conformance checking in a regulatory environment. Comments Postprint version. Presented at AbstractAs software becomes ever more ubiquitous and complex in medical devices, it becomes increasingly important to assure that it performs safely and effectively. The critical nature of medical devices necessitates that the software used therein be reliable and free of errors. It becomes imperative, therefore, to have a conformance review process in place to ascertain the correctness of the software and to ensure that it meets all requirements and standards.Formal methods have long been suggested as a means to design and develop medical device software. However, most manufacturers shy from using these techniques, citing them as too complex and time consuming. As a result, (potentially life-threatening) errors are often not discovered until a device is already on the market.In this paper we present a reference model based approach to software conformance checking. Reference models enable the application of formal methods to software conformance checking, and provide a framework for rigorous testing. To illustrate the approach, we develop the reference model for a Generic Patient Controlled Analgesic Infusion Pump, and explain how it can be used to aid software conformance checking in a regulatory environment.
Abstract-Medical devices have been changing in revolutionary ways in recent years. One is in their form-factor. Increasing miniaturization of medical devices has made them wearable, light-weight, and ubiquitous; they are available for continuous care and not restricted to clinical settings. Further, devices are increasingly becoming connected to external entities through both wired and wireless channels. These two developments have tremendous potential to make healthcare accessible to everyone and reduce costs. However, they also provide increased opportunity for technology savvy criminals to exploit them for fun and profit. Consequently, it is essential to consider medical device security issues.In this paper, we focused on the challenges involved in securing networked medical devices. We provide an overview of a generic networked medical device system model, a comprehensive attack and adversary model, and describe some of the challenges present in building security solutions to manage the attacks. Finally, we provide an overview of two areas of research that we believe will be crucial for making medical device system security solutions more viable in the long run: forensic data logging, and building security assurance cases.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.