Prediction of the Artificial Heart Beat Using Machine Learning Algorithms

Authors

  • Oulfat Jolaha Tishreen University
  • Lody Bashour Tishreen University

Keywords:

Artificial heart, Machine Learning algorithms, Linear Regression, Support Vector Regression, K-Neighbors Regressor.

Abstract

An artificial heart is a device that replaces the natural heart, and it is usually used as a temporary means for gaining time during heart transplantation, or it is used permanently in cases where it is difficult to do the heart transplantation. In this paper, a system for predicting the heart beat is designed based on blood oxygen saturation level SPO2, respiratory rate, and pulse rate using three machine learning algorithms, which are: Linear Regression, Support Vector Regression, and K-Neighbors Regressor. It is found that the K-Neighbors Regressor algorithm gives lower error rate in the number of artificial heartbeats compared with the other algorithms in different physiological conditions that person may experience.

 

Author Biographies

Oulfat Jolaha, Tishreen University

Assistant Professor, Department of Computers and Automatic Control, Faculty of Mechanical and Electrical Engineering

Lody Bashour, Tishreen University

Postgraduate Student (Master), Department of Computers and Automatic Control, Faculty of Mechanical and Electrical Engineering

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Published

2021-11-07

How to Cite

1.
جولحة ا, بشور ل. Prediction of the Artificial Heart Beat Using Machine Learning Algorithms. Tuj-eng [Internet]. 2021Nov.7 [cited 2025Jan.22];43(5). Available from: https://journal.tishreen.edu.sy/index.php/engscnc/article/view/11021

Issue

Vol. 43 No. 5 (2021): Tishreen University Journal of Research and Scientific Studies - Engineering Sciences Series

Section

Master student researches

License

Copyright (c) 2021 ttps://creativecommons.org/licenses/by-nc-sa/4.0/

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