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Detection of QRS Complex with the Use of Matched Filtering

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Innovations in Biomedical Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 526))

Abstract

In recent years the ECG signal feature parameters play an important role in diagnosing, forecasting and analyzing heart diseases. In this paper, we present a new approach for using matched filtering method for the purpose of QRS complex detection. The method is based on the following steps: pre-processing, matched filtering and algorithm for QRS complex detection. To evaluate the proposed technique, the well known Physiobank Database: the PTB Diagnostic ECG database has been used. The proposed algorithm allows to achieve high detection of R-peak in ECG signal, as it will be shown in the last section. The application of the new method is a simple and efficient way to improve the accuracy of removal artefacts in ECG signal and QRS complex detection.

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Authors and Affiliations

  1. Faculty of Telecommunications, Computer Sciences and Electrical Engineering, University of Science and Technology, al. prof. S. Kaliskiego 7, 85-789, Bydgoszcz, Poland

    Sandra Śmigiel & Tomasz Marciniak

Authors
  1. Sandra Śmigiel
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  2. Tomasz Marciniak
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Corresponding author

Correspondence to Sandra Śmigiel .

Editor information

Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Marek Gzik

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Ewaryst Tkacz

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Zbigniew Paszenda

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Ewa Piętka

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Śmigiel, S., Marciniak, T. (2017). Detection of QRS Complex with the Use of Matched Filtering. In: Gzik, M., Tkacz, E., Paszenda, Z., Piętka, E. (eds) Innovations in Biomedical Engineering. Advances in Intelligent Systems and Computing, vol 526. Springer, Cham. https://doi.org/10.1007/978-3-319-47154-9_36

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  • DOI: https://doi.org/10.1007/978-3-319-47154-9_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47153-2

  • Online ISBN: 978-3-319-47154-9

  • eBook Packages: EngineeringEngineering (R0)

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