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A Fuzzy Based Gaussian Weighted Moving Windowing for Denoising Electrocardiogram (ECG) Signals

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13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018 (ICAFS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 896))

Abstract

The electrocardiogram is a graphical record of the biological signal that is thought to be susceptible to electrical activity of the heart and utilized in order to clinical diagnosis. Electrocardiogram signal is very responsive in nature, and even if there is small noise mixed with the original signal, assorted characteristics of signal change. ECG signal voltage level is as low as 0.5 to 5 mV and is sensitive to artifacts larger than this. Human electrocardiogram signal range frequency ingredients from 0.05 Hz to 100 Hz and are related to noise, muscle movements, network current, and ambient electromagnetic interference. Electrocardiogram is a very significant sign detects abnormal heart rhythms and examines cause of chest pain and widely utilized in cardiology. Most digital signals are infinitely large or too large to be manipulated as a whole. Because statistical calculations require that all points be present for analysis, it is difficult to statistically analyze sufficiently large signals. To avoid these problems, engineers characteristically analyze small subsets of the aggregate data with an operation named windowing. Fuzzy logic is a mathematical logic that attempts to solve problems with a clear, uncertain data spectrum that makes it possible to obtain a series of correct results. This manuscript suggests denoising method Gaussian Weighted Moving Windowing for denoising Electrocardiogram signals to remove random noise. This study is interpreted with the actual data set and confirmed according to Peak signal to noise ratio.

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Near East University, Near East Boulevard, P.O. Box: 99138, Nicosia, Mersin 10, TRNC, Turkey

    Cemal Kavalcıoğlu & Bülent Bilgehan

Authors
  1. Cemal Kavalcıoğlu
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  2. Bülent Bilgehan
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Corresponding author

Correspondence to Cemal Kavalcıoğlu .

Editor information

Editors and Affiliations

  1. Joint MBA Program, Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    Rafik A. Aliev

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  4. Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA

    Mo. Jamshidi

  5. Department of Mechatronics, Near East University, Nicosia TRNC, Turkey

    Fahreddin M. Sadikoglu

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Kavalcıoğlu, C., Bilgehan, B. (2019). A Fuzzy Based Gaussian Weighted Moving Windowing for Denoising Electrocardiogram (ECG) Signals. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_18

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