Jiang, Zhihao
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Publication Computer Aided Clinical Trials for Implantable Cardiac Devices(2016-08-19) Abbas, Houssam; Jiang, Zhihao; Jang, Kuk Jin; Beccani, Marco; Liang, Jackson; Dixit, Sanjay; Mangharam, RahulIn this effort we investigate the design and use of physiological and device models to conduct pre-clinical trials to provide early insight in the design and execution of the actual clinical trial. Computer models of physiological phenomena like cardiac electrical activity can be extremely complex. However, when the purpose of the model is to interact with a medical device, then it becomes sufficient to model the measurements that the device makes, e.g. the intra-cardiac electrograms (EGMs) that an Implantable Cardioverter Defibrillator (ICD) measures. We present a probabilistic generative model of EGMs, capable of generating exemplars of various arrhythmias. The model uses deformable shape templates, or motifs, to capture the variability in EGM shapes within one EGM channel, and a cycle length parameter to capture the variability in cycle length in one EGM channel. The relation between EGM channels, which is essential for determining whether the current arrhythmia is potentially fatal, is captured by a time-delayed Markov chain, whose states model the various combinations of (learned) motifs. The heart model is minimally parameterized and is learned from real patient data. Thus the statistics of key features reflect the statistics of a real cohort, but the model can also generate rare cases and new combinations from the inferred probabilities. On the device end, algorithms for signal sensing, detection and discrimination for major ICD manufacturers have been implemented both in simulation and on hardware platforms. The generated arrhythmia episodes are used as input to both the modeled ICD algorithms and real ICDs as part of a Computer Aided Clinical Trial (CACT). In a CACT, a computer model simulates the inputs to the device (such as a new, investigational ICD), and the device’s performance is evaluated. By incorporating these results into the appropriate statistical framework, the Computer Aided Clinical Trial results can serve as regulatory evidence when planning and executing an actual clinical trial. We demonstrate this by conducting a mock trial similar to the 2005-2010 RIGHT trial which compared the discrimination algorithms from two major ICD manufacturers. The results of the CACT clearly demonstrate that the failed outcome of the RIGHT trial could have been predicted and provides statistical support for deeper results that could have been captured prior to the trial.Publication Real-time Heart Model for Implantable Cardiac Device Validation and Verification(2010-01-20) Jiang, Zhihao; Pajic, Miroslav; Connolly, Allison T; Dixit, Sanjay; Mangharam, RahulDesigning bug-free medical device software is dif- ficult, especially in complex implantable devices that may be used in unanticipated contexts. Safety recalls of pacemakers and implantable cardioverter defibrillators due to firmware problems between 1990 and 2000 affected over 200,000 devices, comprising 41% of the devices recalled and are increasing in frequency. There is currently no formal methodology or open experimental platform to validate and verify the correct operation of medical device software. To this effect, a real-time Virtual Heart Model (VHM) has been developed to model the electrophysiological operation of the functioning (i.e. during normal sinus rhythm) and malfunctioning (i.e. during arrhythmia) heart. We present a methodology to extract timing properties of the heart to construct a timed-automata model. The platform exposes functional and formal interfaces for validation and verification of implantable cardiac devices. We demonstrate the VHM is capable of generating clinically-relevant response to intrinsic (i.e. premature stimuli) and external (i.e. artificial pacemaker) signals for a variety of common arrhythmias. By connecting the VHM with a pacemaker model, we are able to pace and synchronize the heart during the onset of irregular heart rhythms. The VHM has also been implemented on a hardware platform for closed-loop experimentation with existing and virtual medical devices. The VHM allows for exploratory electrophysiology studies for physicians to evaluate their diagnosis and determine the appropriate device therapy. This integrated functional and formal device design approach will potentially help expedite medical device certification for safer operation.Publication Model-Based Conformance Testing for Implantable Pacemakers(2013-07-31) Chen, George; Jiang, Zhihao; Mangharam, RahulPublication Heart-on-a-Chip: A Closed-loop Testing Platform for Implantable Pacemakers(2014-07-02) Jiang, Zhihao; Radhakrishnan, Sriram; Sampath, Varun; Sarode, Shilpa; Mangharam, RahulImplantable 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.Publication Technical Report: Abstraction-Tree For Closed-loop Model Checking of Medical Devices(2015-05-06) Jiang, Zhihao; Abbas, Houssam; Mosterman, Pieter J; Mangharam, RahulPublication Automated Closed-Loop Model Checking of Implantable Pacemakers using Abstraction Trees(2016-03-16) Jiang, Zhihao; Abbas, Houssam; Mosterman, Pieter; Mangharam, RahulAutonomous medical devices such as implantable cardiac pacemakers are capable of diagnosing the patient condition and delivering therapy without human intervention. Their ability to autonomously affect the physiological state of the patient makes them safety-critical. Sufficient evidence for the safety and efficacy of the device software, which makes these autonomous decisions, should be provided before these devices can be released on the market. Formal methods like model checking can provide safety evidence that the devices can safely operate under a large variety of physiological conditions. The challenge is to develop physiological models that are general enough to cover the large variability of human physiology, and also expressive enough to provide physiological contexts to counter-examples returned by the model checker. In this paper, the authors develop a set of physiological abstraction rules that introduce physiological constraints to heart models. By applying these abstraction rules to a initial set of heart models, an abstraction tree is created. The root model covers all possible inputs to a pacemaker and derived models cover inputs from different heart conditions. If a counter-example is returned by the model checker, the abstraction tree is traversed so that the most concrete counter-example(s) with physiological contexts can be returned to the domain experts for validity check. The abstraction tree framework replaces the manual abstraction and refinement framework, which reduced the amount of domain knowledge required to perform closed-loop model checking. It encourages the use of model checking during the development of autonomous medical devices, and identifies safety risks earlier in the design process.Publication Model-Based Closed-Loop Testing of Implantable Pacemakers(2011-03-01) Jiang, Zhihao; Pajic, Miroslav; Mangharam, RahulThe increasing complexity of software in implantable medical devices such as cardiac pacemakers and defibrillators accounts for over 40% of device recalls. Testing remains the principal means of verification in the medical device certification regime. Traditional software test generation techniques, where the tests are generated independently of the operational environment, are not effective as the device must be tested within the context of the patient's condition and the current state of the heart. It is necessary for the testing system to observe the system state and conditionally generate the next input to advance the purpose of the test. To this effect, a set of general and patient condition-specific temporal requirements is specified for the closed-loop heart and pacemaker system. Based on these requirements, we describe a closed-loop testing environment between a timed automata-based heart model and a pacemaker. This allows for interactive and physiologically relevant model-based test generation for basic pacemaker device operations such as maintaining the heart rate and atrial-ventricle synchrony. We also demonstrate the flexibility and efficacy of the testing environment for more complex common timing anomalies such as reentry circuits, pacemaker mode switch operation and pacemaker-mediated tachycardia. This system is a step toward a testing approach for medical cyber-physical systems with the patient-in-the-loop.Publication Computer Aided Clinical Trials for Implantable Cardiac Devices(2018-07-12) Jang, Kuk Jin; Weimer, James; Abbas, Houssam; Jiang, Zhihao; Liang, Jackson; Dixit, Sanjay; Mangharam, RahulIn this paper we aim to answer the question, ``How can modeling and simulation of physiological systems be used to evaluate life-critical implantable medical devices?'' Clinical trials for medical devices are becoming increasingly inefficient as they take several years to conduct, at very high cost and suffer from high rates of failure. For example, the Rhythm ID Goes Head-to-head Trial (RIGHT) sought to evaluate the performance of two arrhythmia discriminator algorithms for implantable cardioverter defibrillators, Vitality 2 vs. Medtronic, in terms of time-to-first inappropriate therapy, but concluded with results contrary to the initial hypothesis - after 5 years, 2,000+ patients and at considerable ethical and monetary cost. In this paper, we describe the design and performance of a computer-aided clinical trial (CACT) for Implantable Cardiac Devices where previous trial information, real patient data and closed-loop device models are effectively used to evaluate the trial with high confidence. We formulate the CACT in the context of RIGHT using a Bayesian statistical framework. We define a hierarchical model of the virtual cohort generated from a physiological model which captures the uncertainty in the parameters and allows for the systematic incorporation of information available at the design of the trial. With this formulation, the CACT estimates the inappropriate therapy rate of Vitality 2 compared to Medtronic as 33.22% vs 15.62% (pPublication Using the Virtual Heart Model to Validate the Mode-Switch Pacemaker Operation(2010-08-31) Jiang, Zhihao; Mangharam, Rahul; Connolly, AllisonArtificial 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.Publication From Verification to Implementation: A Model Translation Tool and a Pacemaker Case Study(2012-01-01) Pajic, Miroslav; Jiang, Zhihao; Lee, Insup; Sokolsky, Oleg; Mangharam, RahulModel-Driven Design (MDD) of cyber-physical systems advocates for design procedures that start with formal modeling of the real-time system, followed by the model’s verification at an early stage. The verified model must then be translated to a more detailed model for simulation-based testing and finally translated into executable code in a physical implementation. As later stages build on the same core model, it is essential that models used earlier in the pipeline are valid approximations of the more detailed models developed downstream. The focus of this effort is on the design and development of a model translation tool, UPP2SF, and how it integrates system modeling, verification, model-based WCET analysis, simulation, code generation and testing into an MDD based framework. UPP2SF facilitates automatic conversion of verified timed automata-based models (in UPPAAL) to models that may be simulated and tested (in Simulink/Stateflow). We describe the design rules to ensure the conversion is correct, efficient and applicable to a large class of models. We show how the tool enables MDD of an implantable cardiac pacemaker. We demonstrate that UPP2SF preserves behaviors of the pacemaker model from UPPAAL to Stateflow. The resultant Stateflow chart is automatically converted into C and tested on a hardware platform for a set of requirements.