Analysis of digital filters for preprocessing biomedical signals from ECG apparatus

• Main Authors: Goryaev, V. M., Uchurova, E. O., Basangova, E. O., Bembitov, D. B., Miloshenko, A. P.
• Format: Conference Proceeding
• Language: English
• Subjects: Algorithms; Arrhythmia; Chebyshev approximation; Digital filters; Digital signal processing; Electrocardiography; Frequency spectrum; Notch filters; Preprocessing; Signal processing; Signal quality; Signal to noise ratio; Smoothness; Spectra
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0125057

Modern biomedical equipment can be immune to various types of noise, but not to basiс noise and power disturbances. These noise sources have frequency spectra that contaminate the corresponding electrocardiogram (ECG) spectra. The digital signal processing algorithms in the preprocessing modules of electrocardiographic apparatus play a key role in providing high quality ECG signals for analysis, interpretation and presentation. Due to the overlap of the signal and noise power spectrum in received ECG data, in frequency selective filters there is a problem between noise removal and the possible deformation of the useful signal. Most importantly, the filtering result should not adversely affect subsequent diagnosis and interpretation. This work carried out a quantitative study of results evaluation between the Remez and Chebyshev filters based on the minimum root-mean-square error, a higher signal-to-noise ratio and peak signal-to-noise ratio 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 and can be used in microcomputer-based arrhythmia monitors.