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Multiadaptive Bionic Wavelet Transform: Application to ECG Denoising and Baseline Wandering Reduction

EURASIP Journal on Advances in Signal Processing20072007:041274

https://doi.org/10.1155/2007/41274

Received: 7 May 2006

Accepted: 11 January 2007

Published: 19 March 2007

Abstract

We present a new modified wavelet transform, called the multiadaptive bionic wavelet transform (MABWT), that can be applied to ECG signals in order to remove noise from them under a wide range of variations for noise. By using the definition of bionic wavelet transform and adaptively determining both the center frequency of each scale together with the -function, the problem of desired signal decomposition is solved. Applying a new proposed thresholding rule works successfully in denoising the ECG. Moreover by using the multiadaptation scheme, lowpass noisy interference effects on the baseline of ECG will be removed as a direct task. The method was extensively clinically tested with real and simulated ECG signals which showed high performance of noise reduction, comparable to those of wavelet transform (WT). Quantitative evaluation of the proposed algorithm shows that the average SNR improvement of MABWT is 1.82 dB more than the WT-based results, for the best case. Also the procedure has largely proved advantageous over wavelet-based methods for baseline wandering cancellation, including both DC components and baseline drifts.

Keywords

Quantum InformationQuantitative EvaluationCenter FrequencyInterference EffectNoise Reduction

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Authors’ Affiliations

(1)
Biomedical Signal and Image Processing Laboratory (BiSIPL), School of Electrical Engineering, Sharif University of Technology, Tehran, Iran

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Copyright

© O. Sayadi and M. B. Shamsollahi. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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