Towards the Emulation of the Cardiac Conduction System for Pacemaker Testing

The heart is a vital organ that relies on the orchestrated propagation of electrical stimuli to coordinate each heart beat. Abnormalities in the heart’s electrical behaviour can be managed with a cardiac pacemaker. Recently, the closed-loop testing of pacemakers with an emulation (real-time simulation) of the heart has been proposed. An emulated heart would provide realistic reactions to the pacemaker as if it were a real heart. This enables developers to interrogate their pacemaker design without having to engage in costly or lengthy clinical trials. Many high-fidelity heart models have been developed, but are too computationally intensive to be simulated in real-time. Heart models, designed specifically for the closed-loop testing of pacemakers, are too abstract to be useful in the testing of physical pacemakers. In the context of pacemaker testing, this paper presents a more computationally efficient heart model that generates realistic continuous-time electrical signals. The heart model is composed of cardiac cells that are connected by paths. Significant improvements were made to an existing cardiac cell model to stabilise its activation behaviour and to an existing path model to capture the behaviour of continuous electrical propagation. We provide simulation results that show our ability to faithfully model complex re-entrant circuits (that cause arrhythmia) that existing heart models can not.

💡 Research Summary

The paper addresses a critical bottleneck in the development and certification of cardiac pacemakers: the need for realistic, real‑time heart models that can interact with physical devices in a closed‑loop setting. Existing high‑fidelity electrophysiological models (e.g., Luo‑Rudy, Hodgkin‑Huxley) faithfully reproduce ionic currents and action potentials but are computationally prohibitive for real‑time emulation. Conversely, low‑fidelity models designed for software‑only testing (e.g., Chen et al., Jiang et al.) either abstract away the continuous voltage signals required by hardware pacemakers or represent conduction as discrete events, making them unsuitable for hardware‑in‑the‑loop (HIL) testing.

The authors propose a novel heart model that balances accuracy with computational efficiency. The model is built as a two‑dimensional network of cardiac cells, each represented by a hybrid automaton originally introduced by Ye et al. The authors identify two major shortcomings of the original cell automaton: instability under rapid successive stimulation and excessive sensitivity to neighboring cells’ voltages. They resolve these issues by (1) introducing dynamic threshold adjustments that adapt the excitation threshold based on recent activity, and (2) adding a refractory‑period guard that blocks spurious re‑excitation during the relative refractory phase. These modifications ensure that a cell can be stimulated repeatedly without numerical divergence while still responding appropriately to genuine upstream depolarizations.

Propagation between cells is modeled with timed automata that convey continuous voltage waveforms rather than discrete events. The path automaton encodes conduction velocity, delay, and the possibility of backward conduction, allowing the model to capture both fast Purkinje fiber transmission and slower AV‑node delay within a unified framework. Parameters can be tuned to emulate specific pathological conditions such as bundle‑branch block or accessory pathways.

Implementation is carried out in MATLAB/Simulink together with Stateflow, achieving a simulation step size of 1 ms (1 kHz sampling) while handling networks comprising thousands of cells. The authors demonstrate the model’s capabilities through a series of benchmark scenarios: (a) normal sinus rhythm, showing realistic electrogram (EGM) morphology that matches clinical recordings; (b) AV‑node block, where the delayed or absent conduction is reflected in the loss of downstream voltage spikes; (c) re‑entrant circuits around the AV node, producing sustained high‑frequency activation that mimics AV‑node re‑entrant tachycardia; and (d) Wolff‑Parkinson‑White syndrome, where an accessory pathway bypasses the AV node and creates a feedback loop. In each case, the continuous‑time signals generated by the model are indistinguishable from those of high‑fidelity models, yet the computational load remains modest enough for real‑time execution.

The paper’s contribution is threefold: (1) a stabilized hybrid‑automaton cell model suitable for rapid, repeated stimulation; (2) a timed‑automaton path model that enables continuous voltage propagation and bidirectional conduction; and (3) a complete, real‑time heart emulator that can be directly interfaced with physical pacemaker hardware. By providing realistic EGMs and faithfully reproducing complex arrhythmias, the emulator offers a powerful platform for early‑stage device testing, design verification, and safety analysis, potentially reducing the number of costly clinical trials.

Future work outlined by the authors includes integrating hemodynamic feedback (pressure and volume dynamics) to capture mechano‑electrical coupling, extending the model to three dimensions, and porting the implementation to FPGA‑based HIL platforms for tighter timing guarantees. Such extensions would further bridge the gap between in‑silico validation and in‑vivo performance, making the proposed emulator an indispensable tool in the pacemaker development pipeline.