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Dependence of sleep apnea detection efficiency on the length of ECG recording

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Advanced Mechatronics Solutions

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 393))

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Abstract

Our computer program allows the calculations of commonly accepted six heart rate variability (HRV) parameters in time domain. Those parameters, obtained from long-time one-channel ECG signal recordings, were used for detection of sleep apnea. The classification model was based on the Support Vector Machines (SVM) method using the discriminative Radial Basis Function (RBF) kernel. The aim of study was to check how the length of analyzed single channel ECG overnight recording influences on accuracy of sleep apnea detection.

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Author information

Authors and Affiliations

  1. Department of Mechatronics, Institute of Precision and Biomedical Engineering, Warsaw University of Technology, Warsaw, Poland

    Agata Pietrzak & Gerard Cybulski

Authors
  1. Agata Pietrzak
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  2. Gerard Cybulski
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Corresponding author

Correspondence to Agata Pietrzak .

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Editors and Affiliations

  1. Institute of Metrology and Biomedical Engineering, Warsaw University of Technology, Warsaw, Poland

    Ryszard Jabłoński

  2. Institute of Automation and Computer Science, Brno University of Technology, Brno, Czech Republic

    Tomas Brezina

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Pietrzak, A., Cybulski, G. (2016). Dependence of sleep apnea detection efficiency on the length of ECG recording. In: Jabłoński, R., Brezina, T. (eds) Advanced Mechatronics Solutions. Advances in Intelligent Systems and Computing, vol 393. Springer, Cham. https://doi.org/10.1007/978-3-319-23923-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-23923-1_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23921-7

  • Online ISBN: 978-3-319-23923-1

  • eBook Packages: EngineeringEngineering (R0)

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