THE ANALYSIS OF APPROXIMATION CHEBYSHEV FOR FILTERS WITH FINITE AND INFINITE IMPULSE CHARACTERISTICS
Modern biomedical equipment may be immune to various types of noise, but not to basic noise and power supply interference. These noise sources have frequency spectra that pollute the corresponding electrocardiogram (ECG) spectra. Digital signal processing algorithms in the preprocessing modules of electrocardiographic devices play a key role in providing high-quality ECG signals for analysis, interpretation and presentation. Due to the overlap of the signal power spectrum and noise in the received ECG data, in frequency-selective filters there is a problem between noise removal and possible deformation of the useful signal. Most importantly, the filtering result should not negatively affect subsequent diagnosis and interpretation. A quantitative study of the evaluation of the results between the Remez and Chebyshev filters was carried out on the basis of the minimum root-mean-square error, a higher value of the signal-to-noise ratio and the peak signal ratio/ noise in a Python environment using a notch filter. The results showed that the noise signal using the Remez filter has a better balance between smoothness and accuracy than the Chebyshev filter. However, the Chebyshev filter has a minimal computational load, respectively, this type of filter will find application in arrhythmia monitors based on microcomputers.