A Novel Emulation Model of the Cardiac Conduction System

Abstract

Models of the cardiac conduction system are usually at two extremes: (1) high fidelity models with excellent precision but lacking a real-time response for emulation (hardware in the loop simulation); or (2) models amenable for emulation, but that do not exhibit appropriate dynamic response, which is necessary for arrhythmia susceptibility. We introduce two abstractions to remedy the situation. The first abstraction is a new cell model, which is a semi-linear hybrid automata. The proposed model is as computationally efficient as current state-of-the-art cell models amenable for emulation. Yet, unlike these models, it is also able to capture the dynamic response of the cardiac cell like the higher-fidelity models. The second abstraction is the use of smooth-tokens to develop a new path model, connecting cells, which is efficient in terms of memory consumption. Moreover, the memory requirements of the path model can be statically bounded and are invariant to the emulation step size. Results show that the proposed semi-linear abstraction for the cell reduces the execution time by up to 44%. Furthermore, the smooth-tokens based path model reduces the memory consumption by 40 times when compared to existing path models. This paves the way for the emulation of complex cardiac conduction systems, using hardware code-generators.