2006
DOI: 10.1007/11731177_12
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Artifact Cancellation from Electrocardiogram by Mixed Wavelet-ICA Filter

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Cited by 6 publications
(6 citation statements)
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“…13,18,30 Both methods reduce the number of source signals by restricting spectral content and employ the virtual channel technique to extract different components from a single observed channel. 20,31 However, other authors maintain that the adaptive function of EMD provides better elimination of interference and better conservation of the target signal than the wavelet in other bio-engineering applications.…”
Section: Combined Methods Based On Emd and Icamentioning
confidence: 99%
See 2 more Smart Citations
“…13,18,30 Both methods reduce the number of source signals by restricting spectral content and employ the virtual channel technique to extract different components from a single observed channel. 20,31 However, other authors maintain that the adaptive function of EMD provides better elimination of interference and better conservation of the target signal than the wavelet in other bio-engineering applications.…”
Section: Combined Methods Based On Emd and Icamentioning
confidence: 99%
“…It can be seen that this process produces ICs with similar morphology to the ECG signal, something that was not possible with the EMD method. After analyzing the correlation of the different ICs with the ECG signal, 3 components of cardiac origin were identified: IC 9 [k], IC 13 [k] y IC 18 [k] (marked by a circle in the figure), since these show a correlation coefficient of 0.44, 0.25 and 0.35, respectively. The rest of the ICs gave a correlation coefficient below 0.20.…”
Section: Intestinal Motility Indexesmentioning
confidence: 99%
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“…In this section we describe the wavelet ICA algorithm, which is used in a variety of contexts, such as medical sciences (e.g., Inuso et al 2007;La Foresta et al 2012;Mammone et al 2012), engineering (e.g., Lin & Zhang 2005), acoustic (e.g., Moussaoui et al 2006;Zhao et al 2006), image denoising (e.g., Karande & Talbar 2014), and astrophysics (e.g., Waldmann 2014).…”
Section: Discrete Wavelet Transform (Dwt)mentioning
confidence: 99%
“…A wavelet analysis is broadly used in modeling non-stationary functional data in that morphological information of data can be captured by a set of wavelet coefficients [19,20,14].…”
Section: Introductionmentioning
confidence: 99%