A stochastic network model of the interaction between cardiac rhythm and artificial pacemaker

Greenhut, Saul E.; Jenkins, Janice M.; MacDonald, R.S.

doi:10.1109/10.245605

Cited by 8 publications

(6 citation statements)

References 15 publications

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“…In [19,34], the authors develop a model of the cardiac conduction system that addresses the stochastic behavior of the heart, validated via simulation. However, the hybrid behavior of the heart is not considered.…”

Section: Related Work Discussion and Conclusionmentioning

confidence: 99%

Invariant Verification of Nonlinear Hybrid Automata Networks of Cardiac Cells

Huang

Fan

Mereacre

et al. 2014

Computer Aided Verification

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Abstract. Verification algorithms for networks of nonlinear hybrid automata (HA) can aid understanding and controling of biological processes such as cardiac arrhythmia, formation of memory, and genetic regulation. We present an algorithm for over-approximating reach sets of networks of nonlinear HA which can be used for sound and relatively complete invariant checking. First, it uses automatically computed input-to-state discrepancy functions for the individual automata modules in the network A for constructing a low-dimensional model M. Simulations of both A and M are then used to compute the reach tubes for A. These techniques enable us to handle a challenging verification problem involving a network of cardiac cells, where each cell has four continuous variables and 29 locations. Our prototype tool can check bounded-time invariants for networks with 5 cells (20 continuous variables, 295 locations) typically in less than 15 minutes for up to reasonable time horizons. From the computed reach tubes we can infer biologically relevant properties of the network from a set of initial states.

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Section: Related Work Discussion and Conclusionmentioning

confidence: 99%

Invariant Verification of Nonlinear Hybrid Automata Networks of Cardiac Cells

Huang

Fan

Mereacre

et al. 2014

Computer Aided Verification

View full text Add to dashboard Cite

show abstract

“…In [13], [23], the authors developed a model of the cardiac conduction system that addresses the stochastic behaviour of the heart, validated via simulation. However, the hybrid behaviour of the heart is not considered.…”

Section: A Related Workmentioning

confidence: 99%

Formal Modelling and Validation of Rate-Adaptive Pacemakers

Kwiatkowska

Lea‐Banks

Mereacre

et al. 2014

2014 IEEE International Conference on Healthcare Informatics

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Rate-adaptive pacemakers make use of sensors in order to automatically adjust the pacing rate according to the metabolic needs of the patient, thus overcoming the limitation of fixed-rate pacemakers that cannot ensure an adequate heart beat in cases of varying physical, mental or emotional activity. This feature significantly improves the quality of life of patients with chronotropic incompetence, i.e. whose heart is unable to increase its rate as the activity increases.We develop a formal model of a rate-adaptive pacemaker based on hybrid automata that explicitly includes sensors for rate control. In particular, we model the VVIR pacemaker with a QT interval sensor, a highly specific metabolic sensor that can sense the exercise activity level, based on the fact that physical (and mental) stresses shorten the QT interval, in turn requiring an increased heart rate. We implement the QT interval sensor through a runtime ECG detection algorithm and validate our model with patient data, showing that the simulated VVIR pacemaker is able to successfully regulate a bradycardia ECG signal and produce a correctly paced heart.The validated rate-adaptive pacemaker is plugged into the model-based framework introduced in [7], which enables rigorous and quantitative verification of closed-loop patient-device systems described as hybrid automata, and supports multiple heart and pacemaker models in a modular way. We demonstrate the usefulness of the framework by performing in silico experiments to demonstrate the correct functioning of rate modulation under different activity levels. Our framework has the potential to reduce the need for exercise testing with real patients.

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“…In [9,18], the authors develop a model of the cardiac conduction system that addresses the stochastic behaviour of the heart, validated via simulation. However, the hybrid behaviour of the heart is not considered.…”

Section: Related Workmentioning

confidence: 99%

“…To remedy this, in this paper we consider so called "failure-to-capture", which in practice is equivalent to insufficient contact between the lead and the myocardium, or lead fracture [9]. In particular, we add to the fixed stimulus current i st (cf.…”

Section: Pacing Noisementioning

confidence: 99%

Quantitative verification of implantable cardiac pacemakers over hybrid heart models

Chen

Diciolla

Kwiatkowska

et al. 2014

Information and Computation

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We develop a model-based framework which supports approximate quantitative verification of implantable cardiac pacemaker models over hybrid heart models. The framework is based on hybrid input-output automata and can be instantiated with user-specified pacemaker and heart models. For the specifications, we identify two property patterns which are tailored to the verification of pacemakers: "can the pacemaker maintain a normal heart behaviour?" and "what is the energy level of the battery after t time units?". We implement the framework in Simulink based on the discrete-time simulation semantics and endow it with a range of basic and advanced quantitative property checks. The advanced property checks include the correction of pacemaker mediated Tachycardia and how the noise on sensor leads influences the pacing level. We demonstrate the usefulness of the framework for safety assurance of pacemaker software by instantiating it with two hybrid heart models and verifying a number of correctness properties with encouraging experimental results.

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A stochastic network model of the interaction between cardiac rhythm and artificial pacemaker

Cited by 8 publications

References 15 publications

Invariant Verification of Nonlinear Hybrid Automata Networks of Cardiac Cells

Invariant Verification of Nonlinear Hybrid Automata Networks of Cardiac Cells

Formal Modelling and Validation of Rate-Adaptive Pacemakers

Quantitative verification of implantable cardiac pacemakers over hybrid heart models

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