Wavelet-Analysis of Cardiosignals Using Matlab
Abstract
This article is devoted to the problem of accurate detection of cardiosignal QRS-complexes for early diagnosis of various diseases of human cardiovascular system. For that purpose various algorithms based on either digital filtering methods or mathematical modeling of ECG signal particular sections are used. However, all listed methods have a number of disadvantages impairing the accuracy of QRS-complex determination. Yet wavelet transforms enabling accurate identification of local features for non-stationary signals are becoming more common in various fields of technology.
The article presents wavelet spectrogram calculation by means of various wavelets and levels of decomposition in the Wavelet Toolbox environment. Based on wavelet coefficient amplitudes, the presence of jumps, discontinuities, i.e. QRS complex can be identified. In addition, by comparing the form of the QRS complex and the graph of the scaling function of different wavelets, the most optimal wavelet is determined for identifying the QRS complex, as well as noise suppression in cardiosignals.
The obtained results can be used not only in electrocardiography, but also in solving problems of identification and processing of various types of signals.
About the Authors
B. F. Badalyan
National Polytechnic University of Armenia
Armenia
Armenia
Ph.D. in Engineering (2010), Associate Professor (2014) of the Department of Radio Devices
The author of more than 30 scientific publications. Area of expertise: error correction coding; mobile radio communication systems; wavelet-analysis of signals; analog and digital electronics; cryptography.
H. A. Gomtsyan
National Polytechnic University of Armenia
Armenia
Armenia
D.Sc. in Engineering (2016), Associate Professor (1986), the Chair of Department of Radio Devices
The author of more than 50 scientific publications. Area of expertise: analog-digital conversion; encoding methods; digital signal processing; mobile communication systems.
S. G. Gomtsyan
National Polytechnic University of Armenia
Armenia
Armenia
External Ph.D. student (2016) of the Department of Radio Devices
The author of 5 scientific publications. Area of expertise: analog and digital electronics; radio-transmitting devices; wavelet-analysis of signals.
References
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2. Ishikawa Y., Mochimaru F. Wavelet Theory-Based Analysis of High-Frequency, High-Resolution Elecrocardiograms: A New Concept for Clinical Uses. Progress in biomedical Research. 2002, vol. 7, no. 3, pp. 179-184.
3. Smolentsev N. K. Veivlet-analiz v MATLAB [Wavelet Analysis in MATLAB]. Moscow, DMK Press, 2010, 448 p. (In Russian)
4. Badalyan B. F., Gomtsyan O. A., Egoyan G. K. Reconstruction of Complex Signals after Multi-Level Wavelet Transform. Materialy 10-i Mezhdunar. nauchno-tekhnich. konferentsii "Sovremennye problemy radiotekhniki i telekommunikatsii" (RT-2014) [X Intern. Scientific and Technical Conf. "Modern Problems of Radio Engineering and Telecommunications]. Sevastopol, 2014, p. 238. (In Russian)
5. Available at: http://feihu.eng.ua.edu/NSF_TUES /w7_1a.pdf (accessed: 26.12.2017).
Review
For citations:
Badalyan B.F., Gomtsyan H.A., Gomtsyan S.G. Wavelet-Analysis of Cardiosignals Using Matlab. Journal of the Russian Universities. Radioelectronics. 2017;(6):5-9. (In Russ.)
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