Feature extraction of electrocardiogram signal using machine learning classification
Abstract
In this article, we'll introduce ways to build virtual worlds through different computer programs. We will show the method of rectangles for analyzing data obtained from the electroencephalogram. We will demonstrate basic mathematical models for movement prediction in a system of virtual reality. Using this data, the main transformations are possible-change of position and rotation (change of orientation).
Keywords
Electrocardiogram (ECG), Machine Learning, Pattern Recognition ,Time-Frequency approach ,PQRST fragments
Full Text:
PDFDOI: http://doi.org/10.11591/ijece.v10i6.pp6598-6605
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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).