# Mathematical Model with Autoregressive Process for Electrocardiogram Signals

## TL;DR

This paper introduces a mathematical model using autoregressive processes and coupled differential equations to simulate electrocardiogram signals, showing good agreement with experimental data.

## Contribution

The work presents a novel autoregressive-based mathematical model for ECG signals, validated against real tachogram data.

## Key findings

- Model accurately replicates ECG signals
- Good agreement with experimental tachogram data
- Demonstrates potential for noninvasive cardiac analysis

## Abstract

The cardiovascular system is composed of the heart, blood and blood vessels. Regarding the heart, cardiac conditions are determined by the electrocardiogram, that is a noninvasive medical procedure. In this work, we propose autoregressive process in a mathematical model based on coupled differential equations in order to model electrocardiogram signals. Our results are compared with experimental tachogram by means of Poincar\'e plot and dentrended fluctuation analysis. We verify that the results from the model with autoregressive process show good agreement with experimental measures from tachogram generated by electrical activity of the heartbeat. With the tachogram we build the electrocardiogram by means of coupled differential equations.