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An Algorithm for Automated Representation of Dynamic Correlation Rhythmograms for Long-lasting Signal Recordings

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Biomedical Engineering Aims and scope

Investigation of the cardiac rhythm in clinical practice makes wide use of 24-hour ECG monitoring. One method for analysis of long-term ECG signal recordings involves representation of the signal as a correlation rhythmogram. Analysis of scattergrams yields statistical data whose processing gives parameters with little information value. These indicators cannot describe dynamic changes in R-R intervals, which contain additional information on the nature of the heartbeat. Our study developed a system for representing signals from long-term ECG traces in the form of dynamic correlation rhythmograms. The algorithm allows changes in heartbeat dynamics over 24 h (or more) to be visualized in less than 1 min. Using the developed system as a tool for visualizing dynamic information on R-R intervals, specialists can extract unique information on the nature of the heartbeat and classify cardiac disorders with greater accuracy.

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Authors and Affiliations

  1. Saint Petersburg Electrotechnical University “LETI”, St. Petersburg, Russia

    P. Yu. Timofeeva, B. E. Alekseev, L. A. Manilo & A. P. Nemirko

Authors
  1. P. Yu. Timofeeva
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  2. B. E. Alekseev
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  3. L. A. Manilo
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  4. A. P. Nemirko
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Corresponding author

Correspondence to P. Yu. Timofeeva.

Additional information

Translated from Meditsinskaya Tekhnika, Vol. 54, No. 5, Sep.-Oct., 2020, pp. 44-47.

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Timofeeva, P.Y., Alekseev, B.E., Manilo, L.A. et al. An Algorithm for Automated Representation of Dynamic Correlation Rhythmograms for Long-lasting Signal Recordings. Biomed Eng 54, 357–360 (2021). https://doi.org/10.1007/s10527-021-10039-5

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  • DOI: https://doi.org/10.1007/s10527-021-10039-5

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