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International Joint Conference on Biomedical Engineering Systems and Technologies

BIOSTEC 2019: Biomedical Engineering Systems and Technologies pp 352–377Cite as

ECGpp: A Framework for Selecting the Pre-processing Parameters of ECG Signals Used for Blood Pressure Classification

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1211))

Abstract

There are many commercially available sensors for acquiring electrocardiogram (ECG) signals, and the predictive analyses are extremely welcome for real-time monitoring in public healthcare. One crucial task of such analysis is the selection of the pre-processing parameters for the ECG signals that carry the most valuable information. For this reason, we extended our previous work by proposing a framework, known as ECGpp, which can be used for selecting the best pre-processing parameters for ECG signals (like signal length and cut-off frequency) that will be involved in predictive analysis. The novelty of the framework is in the evaluation methodology that is used, where an ensemble of performance measures are used to rank and select the most promising parameters. Thirty different combinations of a signal length and a cut-off frequency were evaluated using a data set that contains data from five commercially available ECG sensors in the case of blood pressure classification. Evaluation results show that a signal length of 30 s carries the most valuable information, while it was demonstrated that lower cut-off frequencies, where the ECG components overlap with the baseline wander noise, can also provide promising results. Additionally, the results were tested according to the selection of the performance measures, and it was shown that they are robust to inclusion and exclusion of correlated measures.

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Acknowledgements

The authors acknowledge the financial support from the Slovenian Research Agency (research core funding No. P2-0098, and project Z2-1867).

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Authors and Affiliations

  1. Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovikj 16, 1000, Skopje, North Macedonia

    Monika Simjanoska

  2. Computer Systems Department, Jožef Stefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia

    Gregor Papa, Barbara Koroušić Seljak & Tome Eftimov

Authors
  1. Monika Simjanoska
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  2. Gregor Papa
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  3. Barbara Koroušić Seljak
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  4. Tome Eftimov
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Corresponding author

Correspondence to Tome Eftimov .

Editor information

Editors and Affiliations

  1. Universidade Nova de Lisboa, Caparica, Portugal

    Ana Roque

  2. Lodz University of Technology, Łódź, Poland

    Arkadiusz Tomczyk

  3. Nice Sophia Antipolis University, Nice Cedex 2, France

    Elisabetta De Maria

  4. University of Bremen, Bremen, Germany

    Felix Putze

  5. University of West Bohemia, Pilsen, Czech Republic

    Roman Moucek

  6. Instituto de Telecomunicações, University of Lisbon, Lisbon, Portugal

    Ana Fred

  7. Universidade Nova de Lisboa, Caparica, Portugal

    Hugo Gamboa

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Simjanoska, M., Papa, G., Koroušić Seljak, B., Eftimov, T. (2020). ECGpp: A Framework for Selecting the Pre-processing Parameters of ECG Signals Used for Blood Pressure Classification. In: Roque, A., et al. Biomedical Engineering Systems and Technologies. BIOSTEC 2019. Communications in Computer and Information Science, vol 1211. Springer, Cham. https://doi.org/10.1007/978-3-030-46970-2_17

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  • DOI: https://doi.org/10.1007/978-3-030-46970-2_17

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