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International Conference on Telecommunications

ICT 2018: ICT Innovations 2018. Engineering and Life Sciences pp 107–119Cite as

Optimizing the Impact of Resampling on QRS Detection

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 940))

Abstract

QRS detection is an essential activity performed on the electrocardiogram signal for finding heartbeat features. Even though there is already a lot of literature on QRS detection, we set a research question to find the dependence of QRS detection performance on the sampling frequency, and, if possible, to find a QRS detector that will be highly efficient at different sampling rates. Our synthesis technique aims to find the optimal value of the threshold parameters that define if the detected peak is artifact, noise or real QRS peak. In addition, we conducted experimental research to find the dependence and estimate the optimal threshold values for the best QRS detection performance. Our approach results with increased QRS detection performance on the original sampling frequency by improving the original Hamilton algorithm. We tested with the MIT-BIH Arrhythmia database. Lastly, QRS detection sensitivity and positive predictive rate are used to evaluate the performance of the algorithm.

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Author information

Authors and Affiliations

  1. Ss. Cyril and Methodius University, Faculty of Computer Science and Engineering, 1000, Skopje, Macedonia

    Marjan Gusev & Ervin Domazet

Authors
  1. Marjan Gusev
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  2. Ervin Domazet
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Corresponding author

Correspondence to Marjan Gusev .

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Editors and Affiliations

  1. Faculty of Computer Science and Engineering, Saints Cyril and Methodius University of Skopje, Skopje, Macedonia

    Slobodan Kalajdziski

  2. Faculty of Computer Science and Engineering, Saints Cyril and Methodius University of Skopje, Skopje, Macedonia

    Nevena Ackovska

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Gusev, M., Domazet, E. (2018). Optimizing the Impact of Resampling on QRS Detection. In: Kalajdziski, S., Ackovska, N. (eds) ICT Innovations 2018. Engineering and Life Sciences. ICT 2018. Communications in Computer and Information Science, vol 940. Springer, Cham. https://doi.org/10.1007/978-3-030-00825-3_10

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  • DOI: https://doi.org/10.1007/978-3-030-00825-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00824-6

  • Online ISBN: 978-3-030-00825-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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