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An adaptive level dependent wavelet thresholding for ECG denoising

Paper ID Volume ID Publish Year Pages File Format Full-Text
5173 346 2014 12 PDF Available
Title
An adaptive level dependent wavelet thresholding for ECG denoising
Abstract

This paper describes the research carried out to eliminate the noise found in ECG signal and cardiac rhythm. For this, ECG signals were collected carefully from BIOPAC data acquisition system and MIT-BIH database. MIT-BIH noise stress test database was used for generating realistic noises. In addition, to get a better denoised ECG, Symlet wavelet was chosen because its scaling function is closely related to the shape of ECG. For denoising ECG signal, a novel modified S-median thresholding technique is proposed and evaluated in this paper. The optimal Symlet wavelet of order 6 and decomposition level of 8 are attained for modified S-median thresholding technique. The evaluation results showed that the proposed system performed better than S-median and other existing techniques in the time domain. The frequency domain analysis also showed the preservation of important phenomena of ECG. The scalogram difference of 0.004% indicates the well preservation of time–frequency information.

Keywords
ECG; MABWT; Modified S-median; Symlet wavelet; Scalogram difference; S-median
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An adaptive level dependent wavelet thresholding for ECG denoising
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biocybernetics and Biomedical Engineering - Volume 34, Issue 4, 2014, Pages 238–249
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
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Any Questions? feel free to contact us