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A Linear Parameter Varying ARX Model for Describing Biomedical Signal Couplings

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Computer Aided Systems Theory – EUROCAST 2019 (EUROCAST 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12014))

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Abstract

Biomedical signal processing frequently deals with information extraction for clinical decision support. A major challenge in this field is to reveal diagnostic information by eliminating undesired interfering influences. In case of the electrocardiogram, e.g., a frequently arising interference is caused by respiration, which possibly superimposes diagnostic information. Respiratory sinus arrhythmia, i.e., the acceleration and deceleration of the heartrate (HR) during inhalation and exhalation, respectively, is a well-known phenomenon, which strongly influences the ECG. This influence becomes even more important, when investigating the so-called heart rate variability, a diagnostically powerful signal derived from the ECG. In this work, we propose a model for capturing the relationship between the HR and the respiration, thereby taking the time-variance of physiological systems into account. To this end, we show that so-called linear parameter varying autoregressive models with exogenous input are well suited for modeling the coupling between the two signals of interest.

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Acknowledgments

This work was supported by the Upper Austrian Medical Cognitive Computing Center (\(\text {MC}^3\)).

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Authors and Affiliations

  1. Institute of Signal Processing, Johannes Kepler University Linz, Linz, Austria

    Carl Böck, Kyriaki Kostoglou, Péter Kovács & Mario Huemer

  2. Department of Anesthesiology and Critical Care Medicine, Kepler University Hospital, Linz, Austria

    Carl Böck & Jens Meier

Authors
  1. Carl Böck
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  2. Kyriaki Kostoglou
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  3. Péter Kovács
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  4. Mario Huemer
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  5. Jens Meier
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Corresponding author

Correspondence to Carl Böck .

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Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Roberto Moreno-Díaz

  2. Johannes Kepler University Linz, Linz, Austria

    Franz Pichler

  3. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Alexis Quesada-Arencibia

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Böck, C., Kostoglou, K., Kovács, P., Huemer, M., Meier, J. (2020). A Linear Parameter Varying ARX Model for Describing Biomedical Signal Couplings. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2019. EUROCAST 2019. Lecture Notes in Computer Science(), vol 12014. Springer, Cham. https://doi.org/10.1007/978-3-030-45096-0_42

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  • DOI: https://doi.org/10.1007/978-3-030-45096-0_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45095-3

  • Online ISBN: 978-3-030-45096-0

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