Sinoatrial Node Cell Model with Autonomic Nervous System Control

Danilo Scepanovic, Harvard/Massachusetts Institute of Technology

Photo of Danilo Scepanovic

A person’s heart rate (HR) is the outcome of a complex interplay between the autonomic nervous system (ANS) and the heart’s sinoatrial node cells (SANCs). In hospitals, HR is the most commonly monitored vital sign, but in some situations it has been shown that the ANS signals provide more clinically-relevant information than HR alone. Because it is desirable to quantify ANS tone non-invasively, this becomes an estimation problem. Unfortunately, the existing methods for estimating ANS tone are fairly rudimentary and as a result their interpretation is difficult and inconsistent. We aim to improve estimation of ANS tone by developing a detailed, biologically accurate model of ANS-SANC interaction and using this model to constrain the estimation problem. In our previous work, we developed a parametric model and estimator of instantaneous HR, which would be further processed to yield ANS tone. We also evaluated a baseline SANC model for parallelizability, which may be necessary to carry out simulations and characterize the system. This poster presents the next phase of the work, where we develop a comprehensive SANC model which includes modulation by the ANS. We verify that the model reproduces experimental recordings made in rabbits, and use available cross-species data to derive a model of human SANCs.

Abstract Author(s): Danilo Scepanovic