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Proceedings ArticleDOI

A novel approach for suppression of powerline interference and impulse noise in ECG signals

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TLDR
A novel approach for addressing both the aforementioned issues in ECG signals employing sub-band decomposition using wavelets analysis and powerline suppression using one-dimensional structuring element is proposed.
Abstract
One of the major problems encountered in recording ECG is the appearance of unwanted distortions induced by power line interference in the electrocardiogram. In addition, infections due to impulse noise leads to variations in the amplitudes which represent the abnormalities associated with the heart. This paper proposes a novel approach for addressing both the aforementioned issues in ECG signals employing sub-band decomposition using wavelets analysis. Morphological filtering is applied to the detail sub-bands for removal of impulse noise using one-dimensional structuring element. Further, the powerline interference is removed using IIR Butterworth filter providing significant reduction in power spectral density levels between 50 to 60 Hz. The finally reconstructed ECG signal yields reasonably good impulse noise as well as powerline suppression using the proposed approach.

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Citations
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Proceedings ArticleDOI

A non-iterative adaptive median filter for image denoising

TL;DR: In this article, a non-iterative adaptive median filter is proposed for denoising images contaminated with impulse noise, which operates in two steps: first, the pixels are segregated as noisy and noise free so that subsequent processing can be carried out only for the noisy pixels only in the next step.
Proceedings ArticleDOI

Removal of noise from electrocardiogram using digital FIR and IIR filters with various methods

TL;DR: In this article, the results of different window-based FIR filters, IIR filter with different approximation methods and their respective waveforms are shown and power spectrum density, signal to noise ratio (SNR) and mean square error (MSE) of both noisy and filtered ECG signals are calculated.

Digital FIR and IIR Filters with Various Methods

TL;DR: It is observed that Digital FIR filter with Kaiser Window in order 56 shows high performance as compared to the other windowing techniques and Digital IIR filter approximation methods.
Book ChapterDOI

Performance Improvement of Decision Median Filter for Suppression of Salt and Pepper Noise

TL;DR: A novel algorithm for performance improvement of decision median filter for suppression of salt and pepper noise in digital images and is capable to suppress noise effectively even with the noise contamination levels as high as 90%.
Proceedings ArticleDOI

REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild

TL;DR: It is demonstrated that Rest produces highly-robust and efficient models that substantially outperform the original full-sized models in the presence of noise and quantitatively observes that Rest allows models to achieve up to 17 × energy reduction and 9 × faster inference.
References
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Journal ArticleDOI

The impact of the MIT-BIH Arrhythmia Database

TL;DR: The history of the database, its contents, what is learned about database design and construction, and some of the later projects that have been stimulated by both the successes and the limitations of the MIT-BIH Arrhythmia Database are reviewed.
Journal ArticleDOI

ECG Signal Denoising By Wavelet Transform Thresholding

TL;DR: A new approach based on the threshold value of ECG signal determination is proposed using Wavelet Transform coefficients using MATLAB software, and better results are obtained for ECG signals by the proposed algorithm.
Journal ArticleDOI

ECG signal conditioning by morphological filtering

TL;DR: In this paper, a modified morphological filtering (MMF) technique is used for signal conditioning in order to accomplish baseline correction and noise suppression with minimum signal distortion.
Journal ArticleDOI

Impulsive noise suppression and background normalization of electrocardiogram signals using morphological operators

TL;DR: An approach to impulsive noise suppression and background normalization of digitized electrocardiogram signals using mathematical morphological operators that incorporate the shape information for a signal is presented.
Journal ArticleDOI

Empirical Mode Decomposition vs. Wavelet Decomposition for the Extraction of Respiratory Signal From Single-Channel ECG: A Comparison

TL;DR: Two techniques of decomposition of the ECG signal into suitable bases of functions are proposed, such as the empirical mode decomposition (EMD) and the wavelet analysis, and performance achieved by applying these algorithms to extract the respiratory waveform shape from single-channel ECG is presented.
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