Modeling Cardiac Pacemaker Malfunctions With the Virtual Heart Model

Implantable cardiac devices such as artificial pacemakers deliver therapies according to the timing information from the heart. Such devices work under the assumptions of perfect sensing, which are: (a) the pacemaker leads remain in place, and (b) the pacing therapy in one chamber (e.g. atrium) is insulated from the other chambers (e.g. ventricles). But there are common cases which violate these assumptions and the mechanisms for imperfect sensing cannot be captured by a simple signal generator. In this paper we use the Penn Virtual Heart Model (VHM) to investigate the spatial and temporal aspects of the electrical conduction system of the heart in a closed-loop with a pacemaker model. We utilize the spatial properties of the heart to model the sensing mechanism, and use clinical cases to show the validity of our sensing model. Such closed-loop evaluation of the pacemaker operation allows for functional testing of pacemaker software, the development of new algorithms for rhythm therapy and also serves as a tool for incoming cardiac electrophysiology fellows

Using the Virtual Heart Model to Validate the Mode-Switch Pacemaker Operation

Artificial pacemakers are one of the most widely-used implantable devices today, with millions implanted worldwide. The main purpose of an artificial pacemaker is to treat bradycardia, or slow heart beats, by pacing the atrium and ventricles at a faster rate. While the basic functionality of the device is fairly simple, there are many documented cases of death and injury due to device malfunctions. The frequency of malfunctions due to firmware problems will only increase as the pacemaker operations become more complex in an attempt to expand the use of the device. One reason these malfunctions arise is that there is currently no methodology for formal validation and verification of medical device software, as there are in the safety-critical domains of avionics and industrial control automation. We have developed a timed-automata based Virtual Heart Model (VHM) to act as platform for medical device software validation and verification. Through a case study involving multiple arrhythmias, this investigation shows how the VHM can be used with closed-loop operation of a pacemaker to validate the necessity and functionality of the complex mode-switch pacemaker operation. We demonstrate the correct pacemaker operation, to switch from one rhythm management mode to another, in patients with supraventricular tachycardias

Heart-on-a-Chip: A Closed-loop Testing Platform for Implantable Pacemakers

Implantable cardiac pacemakers restore normal heart rhythm by delivering external electrical pacing to the heart. The pacemaker software is life-critical as the timing of the pulses determine its ability to control the heart rate. Recalls due to software issues have been on the rise with the increasing complexity of pacing algorithms. Open-loop testing remains the primary approach to evaluate the safety of pacemaker software. While this tests how the pacemaker responds to stimulus, it cannot reveal pacemaker malfunctions which drive the heart into an unsafe state over multiple cycles. To evaluate the safety and efficacy of pacemaker software we have developed a heart model to generate different heart conditions and interact with real pacemakers. In this paper, we introduce the closed-loop testing platform which consists of a programmable hardware implementation of the heart that can interact with a commercial pacemaker in closed-loop. The heart-on-a-chip implementation is automatically generated from the Virtual Heart Model in Simulink which models different heart conditions. We describe a case study of Endless Loop Tachycardia to demonstrate potential closed-loop pacemaker malfunctions which inappropriately increase the heart rate. The test platform is part of our model-based design framework for verification and testing of medical devices with the patient--in-the-loop

High-Confidence Medical Device Software Development

The design of bug-free and safe medical device software is challenging, especially in complex implantable devices. This is due to the device\u27s closed-loop interaction with the patient\u27s organs, which are stochastic physical environments. The life-critical nature and the lack of existing industry standards to enforce software validation make this an ideal domain for exploring design automation challenges for integrated functional and formal modeling with closed-loop analysis. The primary goal of high-confidence medical device software is to guarantee the device will never drive the patient into an unsafe condition even though we do not have complete understanding of the physiological plant. There are two major differences between modeling physiology and modeling man-made systems: first, physiology is much more complex and less well-understood than man-made systems like cars and airplanes, and spans several scales from the molecular to the entire human body. Secondly, the variability between humans is orders of magnitude larger than that between two cars coming off the assembly line. Using the implantable cardiac pacemaker as an example of closed-loop device, and the heart as the organ to be modeled, we present several of the challenges and early results in model-based device validation. We begin with detailed timed automata model of the pacemaker, based on the specifications and algorithm descriptions from Boston Scientific. For closed-loop evaluation, a real-time Virtual Heart Model (VHM) has been developed to model the electrophysiological operation of the functioning and malfunctioning (i.e., during arrhythmia) hearts. By extracting the timing properties of the heart and pacemaker device, we present a methodology to construct timed-automata models for formal model checking and functional testing of the closed-loop system. The VHM\u27s capability of generating clinically-relevant response has been validated for a variety of common arrhythmias. Based on a set of requirements, we describe a framework of Abstraction Trees that allows for interactive and physiologically relevant closed-loop model checking and testing for basic pacemaker device operations such as maintaining the heart rate, atrial-ventricle synchrony and complex conditions such as avoiding pacemaker-mediated tachycardia. Through automatic model translation of abstract models to simulation-based testing and code generation for platform-level testing, this model-based design approach ensures the closed-loop safety properties are retained through the design toolchain and facilitates the development of verified software from verified models. This system is a step toward a validation and testing approach for medical cyber-physical systems with the patient-in-the-loop

Closed-loop Verification of Medical Devices With Model Abstraction and Refinement

The design and implementation of software for medical devices is challenging due to the closed-loop interaction with the patient, which is a stochastic physical environment. The safety-critical nature and the lack of existing industry standards for verification, make this an ideal domain for exploring applications of formal modeling and closed-loop analysis. The biggest challenge is that the environment model(s) have to be both complex enough to express the physiological requirements, and general enough to cover all possible inputs to the device. In this effort, we use a dual chamber implantable pacemaker as a case study to demonstrate verification of software specifications of medical devices as timed-automata models in UPPAAL. The pacemaker model is based on the specifications and algorithm descriptions from Boston Scientific. The heart is modeled using timed automata based on the physiology of heart. The model is gradually abstracted with timed simulation to preserve properties. A manual Counter-Example-Guided Abstraction and Refinement (CEGAR) framework has been adapted to refine the heart model when spurious counter-examples are found. To demonstrate the closed-loop nature of the problem and heart model refinement, we investigated two clinical cases of Pacemaker Mediated Tachycardia and verified their corresponding correction algorithms in the pacemaker. Along with our tools for code generation from UPPAAL models, this effort enables model-driven design and certification of software for medical devices

From Verified Models to Verified Code for Safe Medical Devices

Medical devices play an essential role in the care of patients around the world, and can have a life-saving effect. An emerging category of autonomous medical devices like implantable pacemakers and implantable cardioverter defibrillators (ICD) diagnose conditions of the patient and autonomously deliver therapies. Without trained professionals in the loop, the software component of autonomous medical devices is responsible for making critical therapeutic decisions, which pose a new set of challenges to guarantee patient safety. As regulation effort to guarantee patient safety, device manufacturers are required to submit evidence for the safety and efficacy of the medical devices before they can be released to the market. Due to the closed-loop interaction between the device and the patient, the safety and efficacy of autonomous medical devices must ultimately be evaluated within their physiological context. Currently the primary closed-loop validation of medical devices is in form of clinical trials, in which the devices are evaluated on real patients. Clinical trials are expensive and expose the patients to risks associated with untested devices. Clinical trials are also conducted after device development, therefore issues found during clinical trials are expensive to fix. There is urgent need for closed-loop validation of autonomous medical devices before the devices are used in clinical trials. In this thesis, I used implantable cardiac devices to demonstrate the applications of model-based approaches during and after device development to provide confidence towards the safety and efficacy of the devices. A heart model structure is developed to mimic the electrical behaviors of the heart in various heart conditions. The heart models created with the model structure are capable of interacting with implantable cardiac devices in closed-loop and can provide physiological interpretations for a large variety of heart conditions. With the heart models, I demonstrated that closed-loop model checking is capable of identifying known and unknown safety violations within the pacemaker design. More importantly, I developed a framework to choose the most appropriate heart models to cover physiological conditions that the pacemaker may encounter, and provide physiological context to counter-examples returned by the model checker. A model translation tool UPP2SF is then developed to translate the pacemaker design in UPPAAL to Stateflow, and automatically generated to C code. The automated and rigorous translation ensures that the properties verified during model checking still hold in the implementation, which justifies the model checking effort. Finally, the devices are evaluated with a virtual patient cohort consists of a large number of heart models before evaluated in clinical trials. These in-silico pre-clinical trials provide useful insights which can be used to increase the success rate of a clinical trial. The work in this dissertation demonstrated the importance and challenges to represent physiological behaviors during closed-loop validation of autonomous medical devices, and demonstrated the capability of model-based approaches to provide safety and efficacy evidence during and after device development

High-Level Analysis of the Impact of Soft-Faults in Cyberphysical Systems

As digital systems grow in complexity and are used in a broader variety of safety-critical applications, there is an ever-increasing demand for assessing the dependability and safety of such systems, especially when subjected to hazardous environments. As a result, it is important to identify and correct any functional abnormalities and component faults as early as possible in order to minimize performance degradation and to avoid potential perilous situations. Existing techniques often lack the capacity to perform a comprehensive and exhaustive analysis on complex redundant architectures, leading to less than optimal risk evaluation. Hence, an early analysis of dependability of such safety-critical applications enables designers to develop systems that meets high dependability requirements. Existing techniques in the field often lack the capacity to perform full system analyses due to state-explosion limitations (such as transistor and gate-level analyses), or due to the time and monetary costs attached to them (such as simulation, emulation, and physical testing). In this work we develop a system-level methodology to model and analyze the effects of Single Event Upsets (SEUs) in cyberphysical system designs. The proposed methodology investigates the impacts of SEUs in the entire system model (fault tree level), including SEU propagation paths, logical masking of errors, vulnerability to specific events, and critical nodes. The methodology also provides insights on a system's weaknesses, such as the impact of each component to the system's vulnerability, as well as hidden sources of failure, such as latent faults. Moreover, the proposed methodology is able to identify and categorize the system's components in order of criticality, and to evaluate different approaches to the mitigation of such criticality (in the form of different configurations of TMR) in order to obtain the most efficient mitigation solution available. The proposed methodology is also able to model and analyze system components individually (system component level), in order to more accurately estimate the component's vulnerability to SEUs. In this case, a more refined analysis of the component is conducted, which enables us to identify the source of the component's criticality. Thereafter, a second mitigation mechanic (internal to the component) takes place, in order to evaluate the gains and costs of applying different configurations of TMR to the component internally. Finally, our approach will draw a comparison between the results obtained at both levels of analysis in order to evaluate the most efficient way of improving the targeted system design

Testing and Validation Framework for Closed-Loop Physiology Management Systems for Critical and Perioperative Care

The research aims at developing a framework for testing systems such as closed-loop physiology management systems to ensure that they are safe and effective for use with patients. Building medical devices that are both robust and safe is a challenge. There has been a tremendous increase in modernization and innovation of various medical systems but many of these systems either fail trials or are recalled due to safety issues. Medical operation rooms require care teams responsible for monitoring the patients and other technical surgical devices. The care process requires a balancing administration that takes care of the drugs and fluids administered to patients. However, the safety and efficacy of these devices have been a concern to many medical practitioners and patients. Due to the complexity of surgical procedures, more fluids are required leading to a necessity of multiple pumps. To help the team in such circumstances, systems called closed loop assistants (CLAs) have been proposed. These systems help by monitoring the patient and possibly adjust infusions while clinicians maintain supervisory control. This thesis provides a framework for testing and validating CLAs through the use of computer simulations of human physiology called in silico patients. A simulated case study based on low blood pressure management in ICU is used to show how the framework can be used in software-only fast simulations or in real-time simulations. The results show that not only can the framework show what a CLA may do in terms of managing physiology but can also give insight as to why. The hope is that this framework will be useful to researchers and practitioners as they develop CLAs since they can test ideas early and often

Magnetic Resonance Imaging on Patients with Implanted Cardiac Pacemakers

The aim of this work was to identify the patterns that can induce heating around implanted cardiac pacemakers during MRI and to develop strategies to counteract them. Two approaches were taken: computer simulations of the occurring electromagnetic field distributions and in-vitro experiments using phantoms in real MRI devices, both for conventional bore-hole and new open MRI systems. Using the open MRI, the observed heating could be reduced significantly