Baseline Wander and Power Line Interference Removal from Physiological Signals Using Fractional Notch Filter Optimized Through Genetic Algorithm

Abstract

Physiological signals commonly suffer from contamination by various types of noise, ones of the most foremost are baseline wander (BLW) and power line interference (PLI). The removal of these interferences is a crucial in biomedical signal processing and diseases diagnosis. This paper introduces a digital fractional notch filter derived from the corresponding anti-notch one and specifically designed for the removal of BLW and PLI from physiological signals. The salient feature of the proposed filter is its capability to eliminate any frequency range only by adjusting the single parameter ν which defines the central frequency of the anti-notch filter. The performance of the filter is closely linked to the fractional order α and the number of samples L used in approximating the ideal fractional filter. Genetic algorithms were employed to determine the optimal values for these parameters (α, L). The proposed filter has been implemented on noisy ECG, EEG, and EMG signals, exhibiting its efficiency in removing unwanted noise. Comparative analysis with existing BLW and PLI removal techniques indicates that the proposed filter outperforms them based on the evaluation metrics employed.