Methods of extracting electrocardiograms from electronic signals and images in the Python environment
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Karaganda State Technical University
Al-Farabi Kazakh National University
Karaganda State University named after Academician E. A. Buketov
Bakhytgul Zholmagambetova   

Karaganda State Technical University
Submission date: 2020-05-07
Final revision date: 2020-08-14
Acceptance date: 2020-08-14
Online publication date: 2020-08-19
Publication date: 2020-09-02
Diagnostyka 2020;21(3):95–101
High-quality signal processing of an electrocardiogram (ECG) is an urgent problem in present day diagnostics for revealing dangerous signs of cardiovascular diseases and arrhythmias in patients. The used methods and programs of signal analysis and classification work with the arrays of points for mathematical modeling that must be extracted from an image or recording of an electrocardiogram. The aim of this work is developing a method of extracting images of ECG signals into a one-dimensional array. An algorithm is proposed based on sequential color processing operations and improving the image quality, masking and building a one-dimensional array of points using Python tools and libraries with open access. The results of testing samples from the MIT/BIH database and comparing images before and after processing show that the signal extraction accuracy is approximately 95 %. In addition, the presented application design is simple and easy to use. The proposed program for analyzing and processing the ECG data has a great potential in the future for the development of more complex software applications for automatic analyzing the data and determining arrhythmias or other pathologies.
The work has been carried out as a part of a grant in 2018-2020 for the project AR05132044 “Development of a Hardware-medical Complex for Assessing the Psycho-physiological Parameters of a Person”.
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