Abbas, Houssam

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Now showing 1 - 10 of 23
  • 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, Rahul
    In 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% (p
  • Publication
    Computer-Aided Design for Safe Autonomous Vehicles
    (2017-05-01) O'Kelly, Matthew; Abbas, Houssam; Mangharam, Rahul
    This paper details the design of an autonomous vehicle CAD toolchain, which captures formal descriptions of driving scenarios in order to develop a safety case for an autonomous vehicle (AV). Rather than focus on a particular component of the AV, like adaptive cruise control, the toolchain models the end-to-end dynamics of the AV in a formal way suitable for testing and verification. First, a domain-specific language capable of describing the scenarios that occur in the day-to-day operation of an AV is defined. The language allows the description and composition of traffic participants, and the specification of formal correctness requirements. A scenario described in this language is an executable that can be processed by a specification-guided automated test generator (bug hunting), and by an exhaustive reachability tool. The toolchain allows the user to exploit and integrate the strengths of both testing and reachability, in a way not possible when each is run alone. Finally, given a particular execution of the scenario that violates the requirements, a visualization tool can display this counter-example and generate labeled sensor data. The effectiveness of the approach is demonstrated on five autonomous driving scenarios drawn from a collection of 36 scenarios that account for over 95% of accidents nationwide. These case studies demonstrate robustness-guided verification heuristics to reduce analysis time, counterexample visualization for identifying controller bugs in both the discrete decision logic and low-level analog (continuous) dynamics, and identification of modeling errors that lead to unrealistic environment behavior.
  • Publication
    Tech Report: Robust Model Predictive Control for Non-Linear Systems with Input and State Constraints Via Feedback Linearization
    (2016-03-15) Pant, Yash Vardhan; Abbas, Houssam; Mangharam, Rahul
    Robust predictive control of non-linear systems under state estimation errors and input and state constraints is a challenging problem, and solutions to it have generally involved solving computationally hard non-linear optimizations. Feedback linearization has reduced the computational burden, but has not yet been solved for robust model predictive control under estimation errors and constraints. In this paper, we solve this problem of robust control of a non-linear system under bounded state estimation errors and input and state constraints using feedback linearization. We do so by developing robust constraints on the feedback linearized system such that the non-linear system respects its constraints. These constraints are computed at run-time using online reachability, and are linear in the optimization variables, resulting in a Quadratic Program with linear constraints. We also provide robust feasibility, recursive feasibility and stability results for our control algorithm. We evaluate our approach on two systems to show its applicability and performance
  • Publication
    A novel programming language to reduce energy consumption by arrhythmia monitoring algorithms in implantable cardioverter-defibrillators
    (2018-05-09) Abbas, Houssam; Mamouras, Konstantinos; Rodionova, Alena; Liang, Jackson; Rajeev, Alur; Dixit, Sanjay; Mangharam, Rahul
  • Publication
    Relaxed decidability and the robust semantics of Metric Temporal Logic
    (2017-02-16) Abbas, Houssam; O'Kelly, Matthew; Mangharam, Rahul
    Relaxed notions of decidability widen the scope of automatic verification of hybrid systems. In quasi-decidability and $\delta$-decidability, the fundamental compromise is that if we are willing to accept a slight error in the algorithm's answer, or a slight restriction on the class of problems we verify, then it is possible to obtain practically useful answers. This paper explores the connections between relaxed decidability and the robust semantics of Metric Temporal Logic formulas. It establishes a formal equivalence between the robustness degree of MTL specifications, and the imprecision parameter $\delta$ used in $\delta$-decidability when it is used to verify MTL properties. We present an application of this result in the form of an algorithm that generates new constraints to the $\delta$-decision procedure from falsification runs, which speeds up the verification run. We then establish new conditions under which robust testing, based on the robust semantics of MTL, is in fact a quasi-semidecision procedure. These results allow us to delimit what is possible with fast, robustness-based methods, accelerate (near-)exhaustive verification, and further bridge the gap between verification and simulation.
  • Publication
    Smooth Operator: Control using the Smooth Robustness of Temporal Logic
    (2017-08-01) Pant, Yash Vardhan; Abbas, Houssam; Mangharam, Rahul
    Modern control systems, like controllers for swarms of quadrotors, must satisfy complex control objectives while withstanding a wide range of disturbances, from bugs in their software to attacks on their sensors and changes in their environments. These requirements go beyond stability and tracking, and involve temporal and sequencing constraints on system response to various events. This work formalizes the requirements as formulas in Metric Temporal Logic (MTL), and designs a controller that maximizes the robustness of the MTL formula. Formally, if the system satisfies the formula with robustness r, then any disturbance of size less than r cannot cause it to violate the formula. Because robustness is not differentiable, this work provides arbitrarily precise, infinitely differentiable, approximations of it, thus enabling the use of powerful gradient descent optimizers. Experiments on a temperature control example and a two-quadrotor system demonstrate that this approach to controller design outper- forms existing approaches to robustness maximization based on Mixed Integer Linear Programming and stochastic heuristics. Moreover, it is not constrained to linear systems.
  • Publication
    Fly-by-Logic: Control of Multi-Drone Fleets with Temporal Logic Objectives
    (2018-03-19) Pant, Yash Vardhan; Abbas, Houssam; Quaye, Rhudii A.; Mangharam, Rahul
    The problem of safe planning and control for multi- drone systems across a variety of missions is of critical impor- tance, as the scope of tasks assigned to such systems increases. In this paper, we present an approach to solve this problem for multi-quadrotor missions. Given a mission expressed in Signal Temporal Logic (STL), our controller maximizes robustness to generate trajectories for the quadrotors that satisfy the STL spec- ification in continuous-time. We also show that the constraints on our optimization guarantees that these trajectories can be tracked nearly perfectly by lower level off-the-shelf position and attitude controllers. Our approach avoids the oversimplifying abstractions found in many planning methods, while retaining the expressiveness of missions encoded in STL allowing us to handle complex spatial, temporal and reactive requirements. Through experiments, both in simulation and on actual quadrotors, we show the performance, scalability and real-time applicability of our method.
  • Publication
    Automated Closed-Loop Model Checking of Implantable Pacemakers using Abstraction Trees
    (2016-03-16) Jiang, Zhihao; Abbas, Houssam; Mosterman, Pieter; Mangharam, Rahul
    Autonomous 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
    Generalized Robust MTL Semantics for Problems in Cardiac Electrophysiology
    (2018-03-01) Abbas, Houssam; Mangharam, Rahul
    Robustness-Guided Falsification (RGF) is an efficient testing technique that tries to find a system execution that violates some formal specification, by minimizing the robustness of the specification over the set of initial conditions of the system. Robustness uses an underlying distance function on the space of system executions. As RGF is applied to new fields like medicine, it is essential to determine whether our distances still capture the domain expert’s intuition of which executions are similar and which are not. Motivated by the problem of testing the algorithms of cardiac defibrillators implanted in millions of patients worldwide, this work develops a (pseudo- )distance function, called conformance, over the space of cardiac signals. By using it to distinguish between fatal and non-fatal arrhythmias obtained from real patients, it is demonstrated that conformance measures the meaningful distance between cardiac signals much better than distances used in medical devices today. Next, conformance is used to re-define the robustness degrees of Metric Temporal Logic (MTL), and it is shown that conformance-based robust semantics of MTL can bound the (conformance-based) robustness degree, thus enabling a principled application of RGF to problems in the cardiac domain, using the appropriate distance notion. Using existing robust semantics based on sup norm can yield incorrect conclusions, with potentially severe consequences to patients.
  • Publication
    A novel programming language to reduce energy consumption by arrhythmia monitoring algorithms in implantable cardioverter-defibrillators
    (2018-05-01) Abbas, Houssam; Mamouras, Konstantinos; Rodionova, Alena; Liang, Jackson; Rajeev, Alur; Dixit, Sanjay; Mangharam, Rahul