Prediction of the Artificial Heart Beat Using Machine Learning Algorithms
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.
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