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Critical Reviews™ in Biomedical Engineering

年間 6 号発行

ISSN 印刷: 0278-940X

ISSN オンライン: 1943-619X

SJR: 0.262 SNIP: 0.372 CiteScore™:: 2.2 H-Index: 56

Indexed in

Fractional Wavelet for R-Wave Detection in ECG Signal

巻 36, 発行 2-3, 2008, pp. 79-91
DOI: 10.1615/CritRevBiomedEng.v36.i2-3.10
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要約

In this paper, we propose a method for the R-wave detection of the QRS complex of the ECG signal using a fractional wavelet. This fractional wavelet is defined, in this context, as the second derivative of the Cole-Cole distribution function of relaxation times, which is widely used in mathematical modeling of fractional order systems. In order to reduce the noise level for the ECG data, our detection algorithm incorporates the proposed fractional wavelet whose parameters are obtained by maximizing the signal-to-noise ratio of the ECG. The scales of this wavelet are chosen based on the spectral characteristics of the ECG. The proposed algorithm performances were evaluated using the MIT-BIH arrhythmia database. The numerical results show that the proposed algorithm achieved a detection rate of about 99.56%.

によって引用された
  1. FERDI YOUCEF, SOME APPLICATIONS OF FRACTIONAL ORDER CALCULUS TO DESIGN DIGITAL FILTERS FOR BIOMEDICAL SIGNAL PROCESSING, Journal of Mechanics in Medicine and Biology, 12, 02, 2012. Crossref

  2. Ferdi Youcef, Fractional order calculus-based filters for biomedical signal processing, 2011 1st Middle East Conference on Biomedical Engineering, 2011. Crossref

  3. Abdelliche F., Charef A., Ladaci S., Complex fractional and complex Morlet wavelets for QRS complex detection, ICFDA'14 International Conference on Fractional Differentiation and Its Applications 2014, 2014. Crossref

  4. Deserno Thomas, Marx Nikolaus, Computational Electrocardiography: Revisiting Holter ECG Monitoring, Methods of Information in Medicine, 55, 04, 2016. Crossref

  5. Houamed Ibtissem, Saidi Lamir, Srairi Fawzi, ECG signal denoising by fractional wavelet transform thresholding, Research on Biomedical Engineering, 36, 3, 2020. Crossref

  6. Mourad Talbi, ECG Denoising Based on 1-D Double-Density Complex DWT and SBWT, in The Stationary Bionic Wavelet Transform and its Applications for ECG and Speech Processing, 2022. Crossref

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