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Wavelet Analysis of Cardiac Electrical Activity Signals

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Biomedical Engineering Aims and scope

To solve important problems of cardiovascular monitoring, effective algorithms for computer processing of electrocardiogram signals (ECS) should be developed on the basis of nonlinear dynamic analysis. ECS can be represented as electric excitation of the conducting nerve network of the heart (CNNH) in the form of solitons of different sizes, taking into account their polarization along the main CNNH branches. Detailed information on the electrical activity in all parts of the four-chamber heart is contained in the self-similar fractal scale-invariant CNNH structure. With the help of wavelet transform, it is possible to represent the structure of the process of excitation of CNNH segments as a system of local extrema of the wavelet diagram of ECS. The wavelet spectrum of ECS has a fractal structure in the form of self-similar waves with scaling 1/f. Each of these waves reflects the excitation of the corresponding CNNH segment. Wavelet representation of the ECS can be used as a tool for detecting various cardiovascular diseases by visualizing skeleton functions of the ECS wavelet transform.

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References

  1. Aldonin, G. M., Robustness in Nature and Technology [in Russian], Radio i Svyaz’, Moscow (2003).

    Google Scholar 

  2. Helmholtz, H., Neuroexcitation Propagation Rate [Russian translation], GIZ, Moscow (1923).

    Google Scholar 

  3. Zudbinov, Yu. I., “ECG abecedary,” Feniks, No. 3, 8 (2003).

  4. Aldonin, G. M., “Nonlinear dynamic models and structural analysis of the conduction system of the heart,” Usp. Sovr. Radioelektron., No. 9, 46-50 (2012).

  5. Aldonin, G. M., Cherepanov, V. V., and Yarygina, O. L., “Self-Organization in a System of Coupled Nonlinear Oscillators,” Radiotekhnika, No. 6, 50-54 (2013).

  6. Aldonin, G. M., “Autonomous monitoring of the main set of parameters of the cardiovascular system,” Biomed. Eng., 46, No. 1, 232-236 (2013).

    Article  Google Scholar 

  7. Aldonin, G. M., Soldatov, A. V., and Popov, A. S., “Structural topological analysis of cardiac conduction system,” Journal of Siberian Federal University. Engineering and Technologies, 7, No. 1, 853-856 (2014).

    Google Scholar 

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Authors and Affiliations

  1. Siberian Federal University, Krasnoyarsk, Russia

    G. M. Aldonin, A. V. Soldatov & V. V. Cherepanov

Authors
  1. G. M. Aldonin
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  2. A. V. Soldatov
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  3. V. V. Cherepanov
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Corresponding author

Correspondence to A. V. Soldatov.

Additional information

Translated from Meditsinskaya Tekhnika, Vol. 52, No. 2, Mar.-Apr., 2018, pp. 37-40.

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Aldonin, G.M., Soldatov, A.V. & Cherepanov, V.V. Wavelet Analysis of Cardiac Electrical Activity Signals. Biomed Eng 52, 120–124 (2018). https://doi.org/10.1007/s10527-018-9796-x

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  • DOI: https://doi.org/10.1007/s10527-018-9796-x

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