Open AccessECG Signals Processing by Using Wavelet Analysis: Diagnostic Capabilities
Author(s) -
Aleksey Chupov,
A. E. Zhdanov,
F. K. Rakhmatullov,
R. F. Rakhmatullov,
A. Yu. Dolganov
Publication year - 2021
Publication title -
ural radio engineering journal
Language(s) - English
Resource type - Journals
eISSN - 2588-0462
pISSN - 2588-0454
DOI - 10.15826/urej.2021.5.4.001
Subject(s) - wavelet , computer science , signal processing , pattern recognition (psychology) , wavelet transform , artificial intelligence , field (mathematics) , parametric statistics , domain (mathematical analysis) , signal (programming language) , data mining , speech recognition , digital signal processing , mathematics , statistics , mathematical analysis , pure mathematics , computer hardware , programming language
The problem of recognition and classification of biomedical signals is a complex problem related to the interdisciplinary field of computer science and medicine. Within the framework of the project implementation of the development of the new defibrillation equipment, it is necessary to solve the problems of analyzing biomedical signals of the electrocardiogram to obtain a diagnostic solution with the possibility of assigning a specific condition to the pathological condition of the patient. This article presents the analysis of electrocardiogram signals, considering the technical aspects of the analysis of multicomponent signals, and describes the diagnostic possibility of wavelet analysis of ECG signals. The paper considers the limited tools of analyzing the electrocardiogram signal, in particular, limitation of parametric data. Wavelet analysis may significantly expand the analysis of signals and transfer them into the time-frequency domain. Thus, the use of various basic functions of the wavelet transform leads to the determination of the additional diagnostically significant information formalized in the parameters extracted from the wavelet scalogram.