Biomimetics (May 2024)

Modeling the Electrical Activity of the Heart via Transfer Functions and Genetic Algorithms

  • Omar Rodríguez-Abreo,
  • Mayra Cruz-Fernandez,
  • Carlos Fuentes-Silva,
  • Mario A. Quiroz-Juárez,
  • José L. Aragón

DOI
https://doi.org/10.3390/biomimetics9050300
Journal volume & issue
Vol. 9, no. 5
p. 300

Abstract

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Although healthcare and medical technology have advanced significantly over the past few decades, heart disease continues to be a major cause of mortality globally. Electrocardiography (ECG) is one of the most widely used tools for the detection of heart diseases. This study presents a mathematical model based on transfer functions that allows for the exploration and optimization of heart dynamics in Laplace space using a genetic algorithm (GA). The transfer function parameters were fine-tuned using the GA, with clinical ECG records serving as reference signals. The proposed model, which is based on polynomials and delays, approximates a real ECG with a root-mean-square error of 4.7% and an R2 value of 0.72. The model achieves the periodic nature of an ECG signal by using a single periodic impulse input. Its simplicity makes it possible to adjust waveform parameters with a predetermined understanding of their effects, which can be used to generate both arrhythmic patterns and healthy signals. This is a notable advantage over other models that are burdened by a large number of differential equations and many parameters.

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