Optimal selection of wavelet basis function applied to ECG signal denoising. Singh, B., N. & Tiwari, A., K. Digital Signal Processing: A Review Journal, 16(3):275-287, 2006.
Optimal selection of wavelet basis function applied to ECG signal denoising [pdf]Paper  abstract   bibtex   
Over the years ElectroCardioGram (ECG) signal has been used to assess the cardiovascular condition of humans. In practice, real time acquisition and transmission of the ECG may contain noise signals superimposed on it. In general, the signal processing algorithms employed for denoising provide optimal performance and eliminate the high frequency noise between any two beats contained in a continuous ECG signal. Despite their optimal performance, the signal processing algorithms significantly attenuate the peaks of characteristics wave of the ECG signal. This paper presents a selection procedure of mother wavelet basis functions applied for denoising of the ECG signal in wavelet domain while retaining the signal peaks close to their full amplitude. The obtained wavelet based denoised ECG signals retain the necessary diagnostics information contained in the original ECG signal. ?? 2006 Elsevier Inc. All rights reserved.
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 title = {Optimal selection of wavelet basis function applied to ECG signal denoising},
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 keywords = {Basis function,DWT,Denoising,ECG,Thresholding},
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 abstract = {Over the years ElectroCardioGram (ECG) signal has been used to assess the cardiovascular condition of humans. In practice, real time acquisition and transmission of the ECG may contain noise signals superimposed on it. In general, the signal processing algorithms employed for denoising provide optimal performance and eliminate the high frequency noise between any two beats contained in a continuous ECG signal. Despite their optimal performance, the signal processing algorithms significantly attenuate the peaks of characteristics wave of the ECG signal. This paper presents a selection procedure of mother wavelet basis functions applied for denoising of the ECG signal in wavelet domain while retaining the signal peaks close to their full amplitude. The obtained wavelet based denoised ECG signals retain the necessary diagnostics information contained in the original ECG signal. ?? 2006 Elsevier Inc. All rights reserved.},
 bibtype = {article},
 author = {Singh, Brij N. and Tiwari, Arvind K.},
 journal = {Digital Signal Processing: A Review Journal},
 number = {3}
}
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