King, Andrew L.
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Publication A Modal Specification Approach for On-Demand Medical Systems(2013-08-21) King, Andrew L.; Sokolsky, Oleg; Lee, Insup; Feng, LuThe on-demand approach, where systems are assembled from components by lay users, has seen success in the consumer electronics industry. Currently, there is growing demand for on-demand capabilities in medical systems so caregivers can create larger medical systems from smaller medical devices. Unlike consumer electronics, medical systems pose challenges for the on-demand approach due to attributes such as device complexity, device variability and safety requirements. In this paper, we propose a formal specification language for on-demand (medical) systems. Our approach is based on the formalism of Modal I/O Automata, which allows system designers to express complex device requirements and can be used to reason about safety and liveness properties of on-demand medical systems directly from their specifications. We illustrate the applicability of our approach through a case study of a closed-loop patient controlled analgesia system.Publication The MIDdleware Assurance Substrate: Enabling Strong Real-Time Guarantees in Open Systems With OpenFlow(2014-06-01) King, Andrew L.; Chen, Sanjian; Lee, InsupMiddleware designed for use in Distributed Real-Time and Embedded (DRE) systems enable cost and development time reductions by providing simple communications abstractions and hiding operating system-level networking API details from developers. While current middleware technologies can hide many low-level details, designers must provide a static configuration for the system’s underlying network in order to achieve required performance characteristics. This has not been a problem for many types of DRE systems where the configuration of the system is relatively fixed from the factory (e.g., aircraft or naval vessels). However for truly open systems (i.e., systems where end users can add or subtract components at runtime) the standard static network configuration approach cannot guarantee that required performance will be met because network resource demands are not fully known a priori. Open systems with stringent performance requirements need middleware that can dynamically manage the underlying network configuration automatically in response to changing demands. Fortunately, recent trends in networking have resulted in a wide variety of networking equipment that expose a standardized low-level interface to their configuration via the OpenFlow protocol. In this paper we discuss how OpenFlow can be leveraged by DRE middleware to automatically provide performance guarantees. In order to make the discussion concrete, we describe the architecture of our prototype middleware MIDAS as well as the details of one example network resource management strategy. We demonstrate the feasibility of our approach via performance assesment of a simple DRE application using our MIDAS and commerically available OpenFlow hardware.Publication Evaluation of a Smart Alarm for Intensive Care Using Clinical Data(2012-08-01) King, Andrew; Fortino, Kelsea; Stevens, Nicholas; Shah, Sachin; Lee, Insup; Fortino-Mullen, MargaretWe describe and report the results of an evaluation of a smart alarm algorithm for post coronary artery bypass graft (CABG) patients. The algorithm (CABG-SA) was applied to vital sign data streams recorded in a surgical intensive care unit (SICU) at a hospital in the University of Pennsylvania Health System. In order to determine the specificity of CABGSA, the alarms generated by CABG-SA were compared against the actual interventions performed by the staff of the critical care unit. Overall, CABG-SA alarmed for 55% of the time relative to traditional alarms while still generating alarms for 12 of the 13 recorded interventions.Publication Foundations for Safety-Critical on-Demand Medical Systems(2016-01-01) King, Andrew LewisIn current medical practice, therapy is delivered in critical care environments (e.g., the ICU) by clinicians who manually coordinate sets of medical devices: The clinicians will monitor patient vital signs and then reconfigure devices (e.g., infusion pumps) as is needed. Unfortunately, the current state of practice is both burdensome on clinicians and error prone. Recently, clinicians have been speculating whether medical devices supporting ``plug & play interoperability'' would make it easier to automate current medical workflows and thereby reduce medical errors, reduce costs, and reduce the burden on overworked clinicians. This type of plug & play interoperability would allow clinicians to attach devices to a local network and then run software applications to create a new medical system ``on-demand'' which automates clinical workflows by automatically coordinating those devices via the network. Plug & play devices would let the clinicians build new medical systems compositionally. Unfortunately, safety is not considered a compositional property in general. For example, two independently ``safe'' devices may interact in unsafe ways. Indeed, even the definition of ``safe'' may differ between two device types. In this dissertation we propose a framework and define some conditions that permit reasoning about the safety of plug & play medical systems. The framework includes a logical formalism that permits formal reasoning about the safety of many device combinations at once, as well as a platform that actively prevents unintended timing interactions between devices or applications via a shared resource such as a network or CPU. We describe the various pieces of the framework, report some experimental results, and show how the pieces work together to enable the safety assessment of plug & play medical systems via a two case-studies.Publication On Effective Testing of Health Care Simulation Software(2011-05-01) Murphy, Christian; Raunak, M. S.; King, Andrew; Chen, Sanjian; Imbriano, Christopher; Kaiser, Gail; Lee, Insup; Sokolsky, Oleg; Clarke, Lori; Osterweil, LeonHealth care professionals rely on software to simulate anatomical and physiological elements of the human body for purposes of training, prototyping, and decision making. Software can also be used to simulate medical processes and protocols to measure cost effectiveness and resource utilization. Whereas much of the software engineering research into simulation software focuses on validation (determining that the simulation accurately models real-world activity), to date there has been little investigation into the testing of simulation software itself, that is, the ability to effectively search for errors in the implementation. This is particularly challenging because often there is no test oracle to indicate whether the results of the simulation are correct. In this paper, we present an approach to systematically testing simulation software in the absence of test oracles, and evaluate the effectiveness of the technique.Publication A Modal Specification Theory for Timing Variability(2013-11-13) King, Andrew; Sokolsky, Oleg; Lee, InsupModal specifications are classical formalisms that can be used to express the functional variability of systems; it is particularly useful for capturing the stepwise refinement of component-based design. However, the extension of such formalisms to real-time systems has not received adequate attention. In this paper, we propose a novel notion of time-parametric modal specifications to describe the timing as well as functional variability of real-time systems.We present a specification theory on modal refinement, property preservation and compositional reasoning. We also develop zone-graph based symbolic methods for the reachability analysis and modal refinement checking. We demonstrate the practical application of our proposed theory and algorithms via a case study of medical device cyber-physical systems.Publication Towards Assurance for Plug & Play Medical Systems(2015-09-01) King, Andrew L.; Feng, Lu; Chen, Sanjian; Sokolsky, Oleg; Lee, Insup; Procter, Sam; Hatcliff, JohnTraditional safety-critical systems are designed and integrated by a systems integrator. The system integrator can asses the safety of the completed system before it is deployed. In medicine, there is a desire to transition from the traditional approach to a new model wherein a user can combine various devices post-hoc to create a new composite system that addresses a specific clinical scenario. Ensuring the safety of these systems is challenging: Safety is a property of systems that arises from the interaction of system components and it’s not possible to asses overall system safety by assessing a single component in isolation. It is unlikely that end-users will have the engineering expertise or resources to perform safety assessments each time they create a new composite system. In this paper we describe a platform-oriented approach to providing assurance for plug & play medical systems as well as an associated assurance argument pattern.Publication Challenges and Research Directions in Medical Cyber-Physical Systems(2012-01-01) Lee, Insup; Sokolsky, Oleg; Chen, Sanjian; Hatcliff, John; Jee, Eunkyoung; Kim, BaekGyu; King, Andrew; Mullen-Fortino, Margaret; Park, Soojin; Roederer, Alexander; Venkatasubramanian, KrishnaMedical cyber-physical systems (MCPS) are lifecritical, context-aware, networked systems of medical devices. These systems are increasingly used in hospitals to provide highquality continuous care for patients. The need to design complex MCPS that are both safe and effective has presented numerous challenges, including achieving high assurance in system software, intoperability, context-aware intelligence, autonomy, security and privacy, and device certifiability. In this paper, we discuss these challenges in developing MCPS, some of our work in addressing them, and several open research issuesPublication Smart Alarms: Multivariate Medical Alarm Integration for Post CABG Surgery Patients(2012-01-01) Stevens, Nicholas; Giannareas, Ana Rosa; Kern, Vanessa; Trevino, Adrian Viesca; Fortino-Mullen, Margaret; King, Andrew; Lee, InsupIn order to monitor patients in the Intensive Care Unit, healthcare practitioners set threshold alarms on each of many individual vital sign monitors. The current alarm algorithms elicit numerous false positive alarms producing an inefficient healthcare system, where nurses habitually ignore low level alarms due to their overabundance. In this paper, we describe an algorithm that considers multiple vital signs when monitoring a post coronary artery bypass graft (post-CABG) surgery patient. The algorithm employs a Fuzzy Expert System to mimic the decision processes of nurses. In addition, it includes a Clinical Decision Support tool that uses Bayesian theory to display the possible CABG-related complications the patient might be undergoing at any point in time, as well as the most relevant risk factors. As a result, this multivariate approach decreases clinical alarms by an average of 59% with a standard deviation of 17% (Sample of 32 patients, 1,451 hours of vital sign data). Interviews comparing our proposed system with the approach currently used in hospitals have also confirmed the potential efficiency gains from this approach.