APPLICATION OF WEIGHTED MYRIAD FILTERS TO SUPPRESS IMPULSIVE NOISE IN BIOMEDICAL SIGNALS

Abstract

Biomedical signals are commonly recorded with many kinds of noise. One of these is a waveform of the electrical activity of muscles. This “natural” distortion is usually modelled with a white Gaussian noise. In order to suppress such noise a weighted myriad filter is applied. The weighted myriad filter belongs to a class of non-linear filters and requires knowledge about noise impulsiveness. An impulsive noise can be described with α-stable distributions. One objective of this paper is to apply α-stable distribution as a model of real-life muscle noise in ECG signals. The other objective of the paper is to apply a weighted myriad filter to suppress impulsive noise in biomedical (ECG) signals. The reference filters have been the Savitzky-Golay smoothing filter and the median filter. The obtained results have shown that α-stable distributions can be applied to model muscle noise and that a weighted myriad filter with a Chebyshev weighted function can effectively suppress such noise.