Electrocardiogram frequency characteristics study by processing and analysis of the signal in time domain and spectral domain
Автор: Chereshnev Vitaly O., Proskurin Sergey G.
Журнал: Cardiometry @cardiometry
Рубрика: Review
Статья в выпуске: 17, 2020 года.
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This paper presents the results of a study in which cardiac signal of the first lead of a standard digital ECG system were processed. By filtering in the time domain, the cardiogram was clarified of noise that reduced influence of spectral harmonics by 10-15%. To present and classify frequency characteristics throughout the entire cardio signal, the QS section between the P and T peaks was smoothed. Due to the influence of sharp peaks on the results of spectral analysis, a result considerably differ from the sum of sinusoidal components is observed. The gap between the peaks is interpolated by the Lagrange polynomial since it did not show an influence on the resultant spectrum. The spectral representation revealed peaks with frequencies oddly even, 3.1 Hz and 6.2 Hz, corresponding to the P and T peaks. Based on the obtained results the frequencies corresponding to the remaining peaks of the cardiogram were also classified. The obtained results represent a spectrum of two regular harmonics what allows for further adequate diagnostics of ECG signals.
Digital electrocardiogram, ecg smoothing, spectral analysis
Короткий адрес: https://sciup.org/148311473
IDR: 148311473 | DOI: 10.12710/cardiometry.2020.17.3033
Список литературы Electrocardiogram frequency characteristics study by processing and analysis of the signal in time domain and spectral domain
- 1. Akselrod S, Gordon D, Ubel FA. Power spectrum analysis of heart rate fluctuation: A quantitative probe of beat-to-beat cardiovascular control. Science. Jour¬nal of Electrocardiology. 1981;213(4504):220–2.
- Ryan SM, Goldberger AL, Ruthazer R. Spectral analysis of heart rate dynamics in elderly persons with postprandial hypotension. The American Journal of Cardiology. 1992;69(3):201–5.
- Mashin VA. Factor analysis of the heart rate spec¬trum. Biophysics. April 2011;56(2):286–97.
- Rudenko M, Zernov V, Voronova O. Fundamental Research on the Mechanism of Cardiovascular Sys-tem Hemodynamics Self-Regulation and Determina¬tion of the Norm-Pathology Boundary for the Basic Hemodynamic Parameters and Analysis of the Com¬pensation Mechanism as a Method of Revealing the Underlying Causes of the Disease. Heart Rhythm. No¬vember 2012;9(11):1909.
- Kulessa B., Srokovski T., Drozdz S. Spectral Prop¬erties of ECG Series. The Henryk Niewodniczanski Institute of Nuclear Physics, Cracow, Poland, Annual Report 2001.
- Soorma N., Singh J., Tiwari M. Feature Extraction of ECG Signal Using HHT Algorithm. Int. Journal of Engineering Trends and Technology (IJETT), 2014; 8 (8): 454-460
- Rangayyan RM. Analysis of biomedical signals. A hands-on approach. Moscow: FIZMATLIT, 2007. 440 p. [in Russian]
- Proskurin SG, Avsievich TI. Spectral analysis of self-oscillating motility in an isolated plasmodial strand of physarum polycephalum. Biophysics. 2014; 59(6):928-934.
- Avdeeva DK., KazakovVY., Natalinova NM., Ivan¬ov ML., Yuzhakova MA., Turushev NV. The simula¬tion results of the high-pass and low-pass filter effect on the quality of micropotential recordings on the elec-trocardiogram // European Journal of Physical and Health Education. 2014(6):P. 1-10.
- Fedotov AA. Selection of Parameters of Band¬pass Filtering of the ECG Signal for Heart Rhythm Mon-itoring Systems // Biomedical Engineering. 2016(50): 114-118.
- Fedotov AA., Akulova AS., Akulov SA. Analysis of the parameters of frequency filtering of an elec-trocar-diograph signal //Measurement Techniques. 2015(57): 1320-1325.