A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds

Mohamed Elgendi, Sivaram Mahalingam, Mirjam Jonkman, Friso De Boer

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

    Abstract

    Automatic QRS Complex detection is important in ECG signal analysis. QRS detection methods are affected by the quality of the ECG recordings and the abnormalities in the ECG signals. In this paper, a generic algorithm is introduced to improve the detection of QRS complexes in Arrhythmia ECG Signals that suffer from: 1) non-stationary effects, 2) low signal-to-noise ratio, 3) negative QRS polarities, 4) low QRS amplitudes, and 5) ventricular ectopics. We compared the algorithm to the method described by Chouhan et al. [16] by applying both algorithms to 19 records of the MIT-BIH database. It was shown that the new algorithm achieves significantly better detection rates resulting in an overall 97.5% sensitivity and 99.9% positive predictivity. � 2008 IEEE.
    Original languageEnglish
    Title of host publicationProceedings - International Symposium on Computer Science and Its Applications, CSA 2008
    Place of PublicationHobart
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages-
    Number of pages6
    Publication statusPublished - 2008
    EventCSA2008. International Symposium on Computer Science and its Applications CSA2008 - Hobart
    Duration: 13 Oct 200815 Oct 2008

    Conference

    ConferenceCSA2008. International Symposium on Computer Science and its Applications CSA2008
    Period13/10/0815/10/08

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    Cite this

    Elgendi, M., Mahalingam, S., Jonkman, M., & De Boer, F. (2008). A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds. In Proceedings - International Symposium on Computer Science and Its Applications, CSA 2008 (pp. -). Hobart: IEEE, Institute of Electrical and Electronics Engineers.