METHODS of EXTRACTING ELECTROCARDIOGRAMS from ELECTRONIC SIGNALS and IMAGES in the PYTHON ENVIRONMENT

被引:0
|
作者
Zholmagambetova B. [1 ]
Mazakov T. [2 ]
Jomartova S. [3 ]
Izat A. [4 ]
Bibalayev O. [5 ]
机构
[1] Department of Information Technology and Security, Karaganda State Technical University, Shakhtarov Avenue, 70-191, Karaganda
[2] Department of Computer Science, Al-Farabi Kazakh National University, Zhanar st. 37a,1, Almaty
[3] Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Zhanar st. 37a,1, Almaty
[4] Department of Applied Mathematics and Computer Science, Karaganda State University named after Academician E. A. Buketov, Shakhtarov Avenue, 70-191, Karaganda
[5] Department of Robotics and Intelligent Machine, Scientific Research Laboratory, Karaganda State University named after Academician E. A. Buketov, Satybaldina str., 16-53, Karaganda
来源
| 1600年 / Polish Society of Technical Diagnostics卷 / 21期
关键词
ECG signal; Image processing; Matplotlib; MIT/BIH; NumPy; One-dimensional array; OpenCV; !text type='Python']Python[!/text;
D O I
10.29354/diag/126398
中图分类号
学科分类号
摘要
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 ECG 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. © 2020 Polish Society of Technical Diagnostics. All rights reserved.
引用
收藏
页码:95 / 101
页数:6
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