Search

Objective: Cardiovascular Implantable Electronic Devices (CIEDs) are used extensively for treating life-threatening conditions such as bradycardia, atrioventricular block and heart failure. The complicated heterogeneous physical dynamics of patients provide distinct challenges to device development and validation. We address this problem by proposing a device testing framework within the in-silico closed-loop context of patient physiology. Methods: We develop an automated framework to validate CIEDs in closed-loop with a high-level physiologically based computational heart model. The framework includes test generation, execution and evaluation, which automatically guides an integrated stochastic optimization algorithm for exploration of physiological conditions. Conclusion: The results show that using a closed loop device-heart model framework can achieve high system test coverage, while the heart model provides clinically relevant responses. The simulated findings of pacemaker mediated tachycardia risk evaluation agree well with the clinical observations. Furthermore, we illustrate how device programming parameter selection affects the treatment efficacy for specific physiological conditions. Significance: This work demonstrates that incorporating model based closed-loop testing of CIEDs into their design provides important indications of safety and efficacy under constrained physiological conditions. [ABSTRACT FROM AUTHOR]

Objective: Evaluating and testing cardiac electrical devices in a closed-physiologic-loop can help design safety, but this is rarely practical or comprehensive. Furthermore, in silico closed-loop testing with biophysical computer models cannot meet the requirements of time-critical cardiac device systems, while simplified models meeting time-critical requirements may not have the necessary dynamic features. We propose a new high-level (abstracted) physiologically-based computational heart model that is time-critical and dynamic. Methods: The model comprises cardiac regional cellular-electrophysiology types connected by a path model along a conduction network. The regional electrophysiology and paths are modeled with hybrid automata that capture non-linear dynamics, such as action potential and conduction velocity restitution and overdrive suppression. The hierarchy of pacemaker functions is incorporated to generate sinus rhythms, while abnormal automaticity can be introduced to form a variety of arrhythmias such as escape ectopic rhythms. Model parameters are calibrated using experimental data and prior model simulations. Conclusion: Regional electrophysiology and paths in the model match human action potentials, dynamic behavior, and cardiac activation sequences. Connected in closed loop with a pacing device in DDD mode, the model generates complex arrhythmia such as atrioventricular nodal reentry tachycardia. Such device-induced outcomes have been observed clinically and we can establish the key physiological features of the heart model that influence the device operation. Significance: These findings demonstrate how an abstract heart model can be used for device validation and to design personalized treatment. [ABSTRACT FROM AUTHOR]

Objective: A flexible, efficient, and verifiable pacemaker cell model is essential to the design of real-time virtual hearts that can be used for closed-loop validation of cardiac devices. A new parametric model of pacemaker action potential is developed to address this need. Methods: The action potential phases are modeled using hybrid automaton with one piecewise-linear continuous variable. The model can capture rate-dependent dynamics, such as action potential duration restitution, conduction velocity restitution, and overdrive suppression by incorporating nonlinear update functions. Simulated dynamics of the model compared well with previous models and clinical data. Conclusion: The results show that the parametric model can reproduce the electrophysiological dynamics of a variety of pacemaker cells, such as sinoatrial node, atrioventricular node, and the His-Purkinje system, under varying cardiac conditions. Significance: This is an important contribution toward closed-loop validation of cardiac devices using real-time heart models. [ABSTRACT FROM PUBLISHER]

This brief proposes a novel adaptive two-level quantizer, which generates 1-b per sample and can be used for a class of industrial networked control systems (NCSs). The adaptive quantizer is introduced to automatically estimate the input of the quantizer using equivalent control-based sliding mode control. The stability condition of the proposed quantizer is derived analytically with the help of a sliding-mode analysis. The effectiveness of the proposed quantized NCS is illustrated experimentally by designing a quantized feedback controller to control the position of a dc motor, where signals with 1-b per sample are utilized to interconnect the controller with the plant. Simulation results from a laboratory prototype illustrate that the proposed quantizer with the feedback controller controls the system effectively, introduces less quantization noise, and minimizes the data rate. [ABSTRACT FROM PUBLISHER]