Feature extraction of electrocardiogram signal using machine learning classification

Sumanta Kuila, Namrata Dhanda, Subhankar Joardar


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).


Electrocardiogram (ECG), Machine Learning, Pattern Recognition ,Time-Frequency approach ,PQRST fragments

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DOI: 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