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Real-time Algorithm for Detection of Atrial Fibrillation

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Biomedical Engineering Aims and scope

One of the objectives of population screening programs is to control and prevent heart disease. This particular problem is solved within the framework of the project CardioQVARK. Among the most important functions of the ECG monitoring equipment is identification of atrial fibrillation (AF), which refers to the most common and dangerous arrhythmias. Today, there are many algorithms to identify this disorder, but the accuracy of the best algorithms does not exceed 94.5%. In this paper, we propose an algorithm based on graphical representation of regularities in the order and length of RR-intervals (distances between adjacent R-waves of the ECG) and consider method for its implementation.

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References

  1. Moody G.B., Mark R.G., Comp. Cardiol., No. 10, 227-230 (1983).

  2. Logan B., Healey J., Comp. Cardiol., 32, 619-622 (2005).

    Google Scholar 

  3. Linker D.T., Long-Term Monitoring for Detection of Atrial Fibrillation: Patent Application Publication, Seattle (2006).

  4. Tatento K., Glass L., Med. Biol. Eng. Comp., 39, 664-671 (2001).

    Article  Google Scholar 

  5. Cerutti S., Mainardi L.T., Porta A., Bianchi A.M., Comp. Cardiol., 24, 77-80 (1997).

    Google Scholar 

  6. Slocum J., Sahakian A., Swiryn S., J. Electrocard., 25, 1-8 (1992).

    Article  Google Scholar 

  7. Schmidt R., Harris M., Novac D., Perkhun M., Atrial Fibrillation Detection: Patent Cooperation Treaty, Eindhoven (2008).

  8. Babaeizadeh S., Gregg R., Helfenbein E., Lindauer J., Zhou S., J. Electrocard., 42, 522-526 (2009).

    Article  Google Scholar 

  9. Couceiro R., Carvalho P., Henriques J., Antunes M., Harris M., Habetha J., 19th Int. Conf. Pat. Recog., Tampa, 1-5 (2008).

  10. Motorina S.V., Kalinichenko A.N., Izv. SPbGETU LETI, No. 10, 55-60 (2014).

  11. Motorina S.V., Kalinichenko A.N., Nemirko A.P. Biotekhnosfera, No. 4, 40, 2-5 (2015).

  12. Physionet: The Research Resource for Physiological Signals (www.physionet.org).

  13. CardioQVARK Project Website: www.cardioqvark.ru

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Authors and Affiliations

  1. St. Petersburg State Electrotechnical University, St. Petersburg, Russia

    S. V. Motorina & A. N. Kalinichenko

  2. Federal Almazov North-West Medical Research Center, St. Petersburg, Russia

    S. V. Motorina

Authors
  1. S. V. Motorina
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  2. A. N. Kalinichenko
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Corresponding author

Correspondence to S. V. Motorina.

Additional information

Translated from Meditsinskaya Tekhnika, Vol. 50, No. 3, May-Jun., 2016, pp. 12-15.

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Motorina, S.V., Kalinichenko, A.N. Real-time Algorithm for Detection of Atrial Fibrillation. Biomed Eng 50, 161–165 (2016). https://doi.org/10.1007/s10527-016-9610-6

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  • DOI: https://doi.org/10.1007/s10527-016-9610-6

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