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Piecewise Modeling of ECG Signals Using Chebyshev Polynomials

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Computational Intelligence in Data Mining

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 711))

Abstract

An electrocardiogram (ECG) signal measures electrical activity of the heart which is used for cardiac-related issues. The morphology of these signals is affected by artifacts during acquisition and transmission which prevents accurate diagnosis. Also a typical ECG monitoring device generates massive volume of digital data which require huge memory and large bandwidth. So there is a need to effectively compress these signals. In this paper, a piecewise efficient model to compress ECG signals is proposed. The model is designed to perform three successive steps: denoising, segmentation, and approximation. Preprocessing is done through total variation denoising technique to reduce noise, while bottom-up time-series approach is implemented to divide the signals into various segments. The individual segments are then approximated using Chebyshev polynomials. The proposed model is compared with other compression models in terms of maximum error, root mean square error, percentage root mean difference, and normalized percentage root mean difference showing significant improvements in performance parameters.

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Authors and Affiliations

  1. Bhilai Institute of Technology Durg, Chhattisgarh, 491001, India

    Om Prakash Yadav & Shashwati Ray

Authors
  1. Om Prakash Yadav
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  2. Shashwati Ray
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Corresponding author

Correspondence to Om Prakash Yadav .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering & Information Technology, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. Department of Computer Science and Engineering, Sri Sivani College of Engineering (SSCE), Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

  3. Department of Computer Application, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Bighnaraj Naik

  4. Machine Intelligence Research (MIR) Lab, Auburn, WA, USA

    Ajith Abraham

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Yadav, O.P., Ray, S. (2019). Piecewise Modeling of ECG Signals Using Chebyshev Polynomials. In: Behera, H., Nayak, J., Naik, B., Abraham, A. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 711. Springer, Singapore. https://doi.org/10.1007/978-981-10-8055-5_26

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