Signal-to-Noise Ratio and Mean Square Error Improving Algorithms Based on Newton Filters for Measurement ECG Data Processing

This article presents the results of analysis of measuring ECG signals processing using two new filtering algorithms for low-frequency and high-frequency interference. The presence of such interferences leads to a decrease in the accuracy of the selection of informative components of the measuring signals. To eliminate low-frequency and high-frequency interference, the results of evaluating the effectiveness of two new algorithms for ECG signals are presented. The processing algorithms are based on a polynomial approximation of the high-pass filter and the wide-band notch filter cascade using Newton polynomials. On the basis of these processing algorithms, its performance was analyzed on a priori models of ECG signals and interference, and on the basis of quantitative indicators, its effectiveness was compared with respect to known algorithms. It was found that processing algorithms based on Newton polynomials significantly improve the quality of filtering of measuring ECG signals and indicators of signal-to-noise ratio and mean square error.