Robust nonlinear aggregation operator for ECG powerline interference reduction. (August 2021)

• Record Type: Journal Article
• Authors: Leski, Jacek M.
• Is Part Of: Biomedical signal processing and control. Volume 69(2021)
• Publication Date: 2021-08
• Subjects: Powerline interference -- Aggregation operator -- Nonlinear filtering -- Robust estimator -- ECG signal; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2021.102675
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: An idea of new nonlinear filters aimed to reduce powerline interference of ECG signals, based on a robust estimator derived from artificial intelligence, is invented. The main advantage of the proposed filters is a substantial reduction in the output signal distortion, crucial for ECG signal processing. The proposed filters can be applied using a computationally efficient algorithm reducing the total cost of ECG signal processing. Higher efficiency of disturbances suppression, lower sensitivity to the values of filter parameters, and the possibility to suppress disturbances of a variable amplitude are among other advantages. Abstract: Objective: Nowadays, the most effective methods for ElectroCardioGraphic (ECG) PowerLine (PL) interference suppression, based on the subtraction operation, require the determination of signal fragments with a low electrical activity of the heart. Any errors in searching for these fragments result in a loss of effectiveness of interference suppression and an increase in signal distortion. This article proposes a method that does not need to determine such signal fragments. Methods: The robust nonlinear aggregation operator is used for the PL disturbance estimation. This results in an automatic reduction (or elimination) of the influence of the ECG signal fragments with an increased electrical activity of the heart. In other words, the samples with the lowest electrical activity of the heart will be used for the PL interference estimation. Results: The method leads to a significant reduction of the ECG signal distortions, unattainable for other methods, leaving the residual noise of the order of single micro-volts, regardless of the PL interference level tackled. The method can be applied using an algorithm that is computationally very efficient, which can help to reduce the total cost of ECG signal processing. The new method proposed is experimentally compared to the traditional ones using signals from the Physikalisch-Technische Bundesanstalt (PTB) diagnostic ECG database. Conclusion: The method proposed is an accurate, robust and computationally efficient algorithm for reduction of PL interference disturbing ECG signals. Significance: New prospects emerge for systems processing the ECG signal, it is possible to analyze traces with a more unfavorable signal-to-noise ratio. This applies to monitoring and exercise systems as well as to a special advanced analysis of e.g. cardiac micro-potentials.