ECG-Derived Respiration Using a Real-Time QRS Detector Based on Empirical Mode Decomposition

Christina Kozia, Randa Herzallah, David Lowe

    Research output: Chapter in Book/Published conference outputConference publication


    Respiration Rate (RR) is an important physiological
    indicator and plays a major role in health deterioration monitoring.
    Despite that, it has been neglected in hospital wards due to
    inadequate nursing skills and insufficient equipment. ECG signal,
    which is always monitored in a clinical setting, is modulated
    by respiration which renders it a highly enticing mean for the
    automatic RR estimation. In addition, accurate QRS detection is
    pivotal to RR estimation from the ECG signal. The investigation
    of QRS complexes is a continuing concern in ECG analysis
    because current methods are still inaccurate and miss heart
    beats. This paper presents a frequency domain RR estimation
    method which uses a novel real-time QRS detector based on
    Empirical Mode Decomposition (EMD). Another novelty of the
    proposed work stems from the RR estimation in the frequency
    domain as opposed to some of the current methods which rely
    on a time domain analysis. As will be shown later, the RR
    extraction in the frequency domain provides more accurate
    results compared to the time domain methods. Moreover, our
    novel QRS detector uses an adaptive threshold over a sliding
    window and differentiates large Q- from R-peaks, facilitating a
    more accurate RR estimation. The performance of our methods
    was tested on real data from Capnobase dataset. An average
    mean absolute error of less than 0.5 breath per minute was
    achieved using our frequency domain method, compared to
    6 breaths per minute of the time domain analysis. Moreover,
    our modified QRS detector shows comparable results to other
    published methods, achieving a detection rate over 99.80%.
    Original languageEnglish
    Title of host publication12th International Conference on Signal Processing and Communication Systems. ICSPCS 2018
    EditorsTadeusz A Wysocki, Beata J Wysocki
    ISBN (Electronic)978-1-5386-5602-0
    ISBN (Print)978-1-5386-5603-7
    Publication statusPublished - 4 Feb 2019
    Event12th International Conference on Signal Processing and Communication Systems, ICSPCS 2018 - Cairns, Australia
    Duration: 17 Dec 201819 Dec 2018


    Conference12th International Conference on Signal Processing and Communication Systems, ICSPCS 2018

    Bibliographical note

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    • ECG-derived-respiration
    • Empirical Mode Decomposition (EMD)
    • Frequency domain analysis
    • Local Signal Energy
    • R-peak detection


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