Research and processing of ECG signals using discrete and continuous wavelet analysis
DOI:
https://doi.org/10.20535/SRIT.2308-8893.2026.2.02Keywords:
electrocardiogram, wavelet transform, packet wavelet filtering, approximation coefficients, detail coefficients, packet filtering, classificationAbstract
The publication is devoted to analyzing electrocardiogram signals of artificial origin of realistic form with the possibility of controlling the duration, sampling frequency, noise level and pulse rate using Ingrid Daubechies wavelets. The synthesized signals were investigated using discrete wavelet analysis to study the influence of these parameters on the approximation and detail coefficients. The priority influence of noise on the detail coefficients and the dependence of the number of signal peaks on the given parameters were established. The article uses for the first time the method of packet discrete wavelet filtering of detail coefficients and approximation coefficients. This allowed to provide a high degree of signal restoration to the original form. Similar studies were conducted for continuous wavelet transformation with the generation of wavelet scalogram images, which provide additional diagnostically significant information. The results obtained in the form of an algorithm are promising for use in analyzing signals from radar systems. The developed model for generating realistic-shaped signals is more efficient and exceeds the average accuracy (96.2 %) compared to analogues (88.03 %). The effectiveness of the developed method is fully confirmed by the correlation matrix of functions of discrete spectra of arti-ficial ECG signals.
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