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A novel method of preprocessing and modeling ECG signals with Lagrange–Chebyshev interpolating polynomials

Author

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  • Om Prakash Yadav

    (PES Institute of Technology and Management)

  • Shashwati Ray

    (Bhilai Institute of Technology)

Abstract

An electrocardiogram (ECG) records electrical potential of the heart and its morphology changes due to the addition of various types of noises during recording which consequently affects accurate analysis and clinical evaluation. Also, due to generation of enormous volume of digital data by ECG monitoring devices, efficient techniques for ECG approximation are necessary for proper data accumulation and transmission, and improved functionality of ECG recorders. Here, we propose a polynomial approximation model which initially enhances the signal quality using total variation optimization; characterizes the enhanced signal through bottom-up method and finally approximates the characterized signal using suitable order Lagrange–Chebyshev interpolation polynomial. The proposed model is tested on MIT-BIH data through standard ECG performance parameters and the results obtained are found to be diagnostically useful.

Suggested Citation

  • Om Prakash Yadav & Shashwati Ray, 2021. "A novel method of preprocessing and modeling ECG signals with Lagrange–Chebyshev interpolating polynomials," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 377-390, June.
    • Handle: RePEc:spr:ijsaem:v:12:y:2021:i:3:d:10.1007_s13198-021-01077-z
    DOI: 10.1007/s13198-021-01077-z
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    References listed on IDEAS

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    1. Guglielmo Caporale & Mario Cerrato, 2010. "Using Chebyshev Polynomials to Approximate Partial Differential Equations," Computational Economics, Springer;Society for Computational Economics, vol. 35(3), pages 235-244, March.
    2. de Leeuw, Jan & Lange, Kenneth, 2009. "Sharp quadratic majorization in one dimension," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2471-2484, May.
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    Cited by:

    1. Vallabhuni Vijay & C. V. Sai Kumar Reddy & Chandra Shaker Pittala & Rajeev Ratna Vallabhuni & M. Saritha & M. Lavanya & S. China Venkateswarlu & M. Sreevani, 2021. "ECG performance validation using operational transconductance amplifier with bias current," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1173-1179, December.

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