Skip to main content

Advertisement

SpringerLink
Log in

Automatic Real Time Detection of Atrial Fibrillation

  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

Atrial fibrillation (AF) is the most common sustained arrhythmia and is associated with significant morbidity and mortality. Timely diagnosis of the arrhythmia, particularly transient episodes, can be difficult since patients may be asymptomatic. In this study, we describe a robust algorithm for automatic detection of AF based on the randomness, variability and complexity of the heart beat interval (RR) time series. Specifically, we employ a new statistic, the Turning Points Ratio, in combination with the Root Mean Square of Successive RR Differences and Shannon Entropy to characterize this arrhythmia. The detection algorithm was tested on two databases, namely the MIT-BIH Atrial Fibrillation Database and the MIT-BIH Arrhythmia Database. These databases contain several long RR interval series from a multitude of patients with and without AF and some of the data contain various forms of ectopic beats. Using thresholds and data segment lengths determined by Receiver Operating Characteristic (ROC) curves we achieved a high sensitivity and specificity (94.4% and 95.1%, respectively, for the MIT-BIH Atrial Fibrillation Database). The algorithm performed well even when tested against AF mixed with several other potentially confounding arrhythmias in the MIT-BIH Arrhythmia Database (Sensitivity = 90.2%, Specificity = 91.2%).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4

Similar content being viewed by others

References

  1. Aytemir, K., S. Aksoyek, A. Yildirir, N. Ozer, and A. Oto. Prediction of atrial fibrillation recurrence after cardioversion by P wave signal-averaged electrocardiography. Int. J. Cardiol. 70:15–21, 1999.

    Article  PubMed  CAS  Google Scholar 

  2. Benjamin, E. J., P. A. Wolf, R. B. D’Agostino, H. Silbershatz, W. B. Kannel, and D. Levy. Impact of atrial fibrillation on the risk of death: the Framingham Heart Study. Circulation 98:946–952, 1998.

    PubMed  CAS  Google Scholar 

  3. Clavier, L., J. M. Boucher, R. Lepage, J. J. Blanc, and J. C. Cornily. Automatic P-wave analysis of patients prone to atrial fibrillation. Med. Biol. Eng. Comput. 40:63–71, 2002.

    Article  PubMed  CAS  Google Scholar 

  4. Defaye, P., F. Dournaux, and E. Mouton. Prevalence of supraventricular arrhythmias from the automated analysis of data stored in the DDD pacemakers of 617 patients: the AIDA study. The AIDA Multicenter Study Group. Automatic Interpretation for Diagnosis Assistance. Pacing Clin. Electrophysiol. 21:250–255, 1998.

    Article  PubMed  CAS  Google Scholar 

  5. Dotsinsky, I. Atrial wave detection algorithm for discovery of some rhythm abnormalities. Physiol. Meas. 28:595–610, 2007.

    Article  PubMed  Google Scholar 

  6. Duverney, D., J. Gaspoz, V. Pichot, F. Roche, R. Brion, A. Antoniadis, and J. Barthélémy. High accuracy of automatic detection of atrial fibrillation using wavelet transform of heart rate intervals. Pacing Clin. Electrophysiol. 25:457–462, 2002.

    Article  PubMed  Google Scholar 

  7. Ehrlich, J. R., K. Schadow, K. Steul, G. Q. Zhang, C. W. Israel, and S. H. Hohnloser. Prediction of early recurrence of atrial fibrillation after external cardioversion by means of P wave signal-averaged electrocardiogram. Z. Kardiol. 92:540–546, 2003.

    Article  PubMed  CAS  Google Scholar 

  8. Fukunami, M., T. Yamada, M. Ohmori, K. Kumagai, K. Umemoto, A. Sakai, N. Kondoh, T. Minamino, and N. Hoki. Detection of patients at risk for paroxysmal atrial fibrillation during sinus rhythm by P wave-triggered signal-averaged electrocardiogram. Circulation 83:162–169, 1991.

    PubMed  CAS  Google Scholar 

  9. Goldberg, R. J. To the framingham data, turn, turn, turn. Circulation 119:1189–1191, 2009.

    Article  PubMed  Google Scholar 

  10. Goldberger, A. L., L. A. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C. K. Peng, and H. E. Stanley. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101:E215–E220, 2000.

    PubMed  CAS  Google Scholar 

  11. Heeringa, J., D. A. van der Kuip, A. Hofman, J. A. Kors, G. van Herpen, B. H. Stricker, T. Stijnen, G. Y. Lip, and J. C. Witteman. Prevalence, incidence and lifetime risk of atrial fibrillation: the Rotterdam study. Eur. Heart J. 27:949–953, 2006.

    Article  PubMed  Google Scholar 

  12. Humphries, K. H., C. R. Kerr, S. J. Connolly, G. Klein, J. A. Boone, M. Green, R. Sheldon, M. Talajic, P. Dorian, and D. Newman. New-onset atrial fibrillation: sex differences in presentation, treatment, and outcome. Circulation 103:2365–2370, 2001.

    PubMed  CAS  Google Scholar 

  13. Israel, C. W., G. Gronefeld, J. R. Ehrlich, Y.-G. Li, and S. H. Hohnloser. Long-term risk of recurrent atrial fibrillation as documented by an implantable monitoring device: implications for optimal patient care. J. Am. Coll. Cardiol. 43:47–52, 2004.

    Article  PubMed  Google Scholar 

  14. Kerr, C., J. Boone, S. Connolly, M. Greene, G. Klein, R. Sheldon, and M. Talajic. Follow-up of atrial fibrillation: the initial experience of the Canadian Registry of Atrial Fibrillation. Eur. Heart J. 17(Suppl C):48–51, 1996.

    PubMed  Google Scholar 

  15. Kinlay, S., J. W. Leitch, A. Neil, B. L. Chapman, D. B. Hardy, and P. J. Fletcher. Cardiac event recorders yield more diagnoses and are more cost-effective than 48-hour Holter monitoring in patients with palpitations. A controlled clinical trial. Ann. Intern. Med. 124:16–20, 1996.

    PubMed  CAS  Google Scholar 

  16. Michalkiewicz, D., M. Dziuk, G. Kaminski, R. Olszewski, M. Cholewa, A. Cwetsch, and L. Markuszewski. Detection of patients at risk for paroxysmal atrial fibrillation (PAF) by signal averaged P wave, standard ECG and echocardiography. Pol. Merkur. Lekarski 20:69–72, 2006.

    PubMed  Google Scholar 

  17. Murgatroyd, F. D., B. Xie, X. Copie, I. Blankoff, A. J. Camm, and M. Malik. Identification of atrial fibrillation episodes in ambulatory electrocardiographic recordings: validation of a method for obtaining labeled r-r interval files. Pacing Clin. Electrophysiol. 18:1315–1320, 1995.

    Article  PubMed  CAS  Google Scholar 

  18. Opolski, G., P. Scislo, J. Stanislawska, G. Aleksander, R. Steckiewicz, and A. Torbicki. Detection of patients at risk for recurrence of atrial fibrillation after successful electrical cardioversion by signal-averaged P-wave ECG. Int. J. Cardiol. 60:181–185, 1997.

    Article  PubMed  CAS  Google Scholar 

  19. Page, R. L., W. E. Wilkinson, W. K. Clair, E. A. McCarthy, and E. L. Pritchett. Asymptomatic arrhythmias in patients with symptomatic paroxysmal atrial fibrillation and paroxysmal supraventricular tachycardia. Circulation 89:224–227, 1994.

    PubMed  CAS  Google Scholar 

  20. Portet, F. P wave detector with PP rhythm tracking: evaluation in different arrhythmia contexts. Physiol. Meas. 29:141–155, 2008.

    Article  PubMed  Google Scholar 

  21. Rawles, J. M., and E. Rowland. Is the pulse in atrial fibrillation irregularly irregular? Br. Heart J. 56:4–11, 1986.

    Article  PubMed  CAS  Google Scholar 

  22. Reddy, S., B. Young, Q. Xue, B. Taha, D. Brodnick, and J. Steinberg. Review of methods to predict and detect atrial fibrillation in post-cardiac surgery patients. J. Electrocardiol. 32(Suppl):23–28, 1999.

    Article  PubMed  Google Scholar 

  23. Roche, F., J. M. Gaspoz, A. Da Costa, K. Isaaz, D. Duverney, V. Pichot, F. Costes, J. R. Lacour, and J. C. Barthélémy. Frequent and prolonged asymptomatic episodes of paroxysmal atrial fibrillation revealed by automatic long-term event recorders in patients with a negative 24-hour Holter. Pacing Clin. Electrophysiol. 25:1587–1593, 2002.

    Article  PubMed  Google Scholar 

  24. Sarkar, S., D. Ritscher, and R. Mehra. A detector for a chronic implantable atrial tachyarrhythmia monitor. IEEE Trans. Biomed. Eng. 55:1219–1224, 2008.

    Article  PubMed  Google Scholar 

  25. Stein, K. M., J. Walden, N. Lippman, and B. B. Lerman. Ventricular response in atrial fibrillation: random or deterministic? Am. J. Physiol. 277:H452–H458, 1999.

    PubMed  CAS  Google Scholar 

  26. Tateno, K., and L. Glass. A method for detection of atrial fibrillation using RR intervals. Comput. Cardiol. 27:391–394, 2000.

    Google Scholar 

  27. Tateno, K., and L. Glass. Automatic detection of atrial fibrillation using the coefficient of variation and density histograms of RR and ΔRR intervals. Med. Biol. Eng. Comput. 39:664–671, 2001.

    Article  PubMed  CAS  Google Scholar 

  28. Wolf, P. A., R. D. Abbott, and W. B. Kannel. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke 22:983–988, 1991.

    PubMed  CAS  Google Scholar 

  29. Zar, J. H. Serial randomness of measurements: nonparametric testing. In: Biostatistical Analysis, 4th edn. Prentice-Hall, 1999, pp. 587–588.

Download references

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, SUNY at Stony Brook, HSC T18, Rm. 030, Stony Brook, NY, 11794, USA

    S. Dash, K. H. Chon & S. Lu

  2. Department of Medicine, Division of Cardiology, SUNY at Stony Brook, Stony Brook, NY, USA

    E. A. Raeder

Authors
  1. S. Dash
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. H. Chon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. E. A. Raeder
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. H. Chon.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dash, S., Chon, K.H., Lu, S. et al. Automatic Real Time Detection of Atrial Fibrillation. Ann Biomed Eng 37, 1701–1709 (2009). https://doi.org/10.1007/s10439-009-9740-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-009-9740-z

Keywords

Search

Navigation