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Erschienen in:

08.02.2024

Design of ECG Denoising Digital Filter Under \(\alpha \)-Stable Noisy Environment Based on Morphological Signal Processing

verfasst von: Aditi Bajaj, Sanjay Kumar

Erschienen in: Circuits, Systems, and Signal Processing | Ausgabe 5/2024

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Abstract

This paper proposes a digital morphological filtering method based on a novel structuring element (SE) formulated using fractional Fourier transform (FrFT) and cross-convolution of window functions. The highlighting feature of this newly formulated filter is its flexibility in adding an adaptive nature to classical morphological filtering. Until now, every method listed in the literature makes a convenient assumption that noises corrupting ECG signal are Gaussian and model the filter around this assumption. Addressing this shortcoming, the first-of-its-kind filter adopts the \(\alpha \)-stable distribution model (of which Gaussian distribution is a special case) of noise to better replicate the real-time noises interfering with ECG signals. The designed filter can suppress the noise and adapt to the changes in ECG signal morphology for better reconstruction. The proposed filter is tested on MIT-BIH Arrhythmia Database. The simulation results show improved performance in several quantitative metrics, demonstrating the superiority of our suggested method over the currently used state-of-the-art techniques.

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Metadaten
Titel
Design of ECG Denoising Digital Filter Under -Stable Noisy Environment Based on Morphological Signal Processing
verfasst von
Aditi Bajaj
Sanjay Kumar
Publikationsdatum
08.02.2024
Verlag
Springer US
Erschienen in
Circuits, Systems, and Signal Processing / Ausgabe 5/2024
Print ISSN: 0278-081X
Elektronische ISSN: 1531-5878
DOI
https://doi.org/10.1007/s00034-024-02602-8