Regulation of Heart Beats by the Autonomous Nervous System in Health and Disease: Point-Process-Theory based Models and Simulation [V-I]

TL;DR

This paper develops a point-process model for heart beat regulation by the autonomic nervous system, incorporating feedback mechanisms, and uses simulations to analyze heart health indicators like the Hurst exponent.

Contribution

It introduces a novel point-process framework that models feedback in heart regulation, providing analytical insights and simulation results for healthy and diseased states.

Findings

Model without feedback allows analytical analysis.

Feedback mechanisms significantly influence heart health indicators.

Simulations demonstrate how nerve activity affects ECG RR intervals.

Abstract

We have advanced a point-process based framework for the regulation of heart beats by the autonomous nervous system and analyzed the model with and without feedback. The model without feedback was found amenable to several analytical results that help develop an intuition about the way the heart interacts with the nervous system. However, in reality, feedback, baroreflex and chemoreflex controls are important to model healthy and unhealthy scenarios for the heart. Based on the Hurst exponent as an index of health of the heart we show how the state of the nervous system may tune it in health and disease. Monte Carlo simulation is used to generate RR interval series of the Electrocardiogram (ECG) for different sympathetic and parasympathetic nerve excitations.