Abstract
Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical research, with a prevalence of 0.4% to 1% of the population. Therefore, the study of AF is an important research field that can provide great treatment improvements. In this paper we apply independent component analysis to a 12-lead electrocardiogram, for which we obtain a 12-source set. We apply to this set three different atrial activity (AA) selection methods based on: kurtosis, correlation of the sources with lead V1, and spectral analysis. We then propose a reliable AA extraction based on the consensus between the three methods in order to reduce the effect of anatomical and physiological variabilities. The extracted AA signal will be used in a future stage for AF classification.
Chapter PDF
Similar content being viewed by others
References
Fuster, V., Rydén, L.E., Cannom, D.S., et al.: ACC/AHA/ESC 2006 Guidelines for the management of patients with atrial fibrillation. Europace 8(9), 651–745 (2006)
Go, A.S., Hylek, E.M., Phillips, K.A., Chang, Y., Henault, L.E., Selby, J.V., Singer, D.E.: Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the anticoagulation and risk factors in atrial fibrillation (atria) study. Journal of the American Medical Association 285(18), 2370–2375 (2001)
Stridh, M., Sornmo, L.: Spatiotemporal qrst cancellation techniques for analysis of atrial fibrillation. IEEE Transactions on Biomedical Engineering 48(1), 105–111 (2001)
Rieta, J.J., Zarzoso, V., Millet-Roig, J., Garcia-Civera, R., Ruiz-Granell, R.: Atrial activity extraction based on blind source separation as an alternative to qrst cancellation for atrial fibrillation analysis. In: Proc. Computers in Cardiology 2000, pp. 69–72 (2000)
Langley, P., Bourke, J.P., Murray, A.: Frequency analysis of atrial fibrillation. In: Proc. Computers in Cardiology 2000. pp. 65–68 (2000)
Rieta, J.J., Castells, F., Sanchez, C., Zarzoso, V., Millet, J.: Atrial activity extraction for atrial fibrillation analysis using blind source separation. IEEE Transactions on Biomedical Engineering 51(7), 1176–1186 (2004)
Phlypo, R., D’Asseler, Y., Lemahieu, I., Zarzoso, V.: Extraction of the atrial activity from the ecg based on independent component analysis with prior knowledge of the source kurtosis signs. In: Proc. 29th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society EMBS 2007, pp. 6499–6502 (2007)
Xiao, J., Chen, Z., Huang, Z.: Atrial activity extraction for atrial fibrillation analysis using mutual information minimization. In: Proc. 1st Int. Conf. Bioinformatics and Biomedical Engineering ICBBE 2007, pp. 916–919 (2007)
Cardoso, J.F.: Source separation using higher order moments. In: Proc. Int. Acoustics, Speech, and Signal Processing ICASSP 1989. Conf., pp. 2109–2112 (1989)
Comon, P.: Independent component analysis, a new concept? Signal Processing 36, 287–314 (1994)
Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley & Sons, Inc. (2001)
Bollmann, A., Husser, D., Mainardi, L., Lombardi, F., Langley, P., Murray, A., Rieta, J.J., Millet, J., Olsson, S.B., Stridh, M., Sörnmo, L.: Analysis of surface electrocardiograms in atrial fibrillation: techniques, research, and clinical applications. Europace 8(11), 911–926 (2006), http://dx.doi.org/10.1093/europace/eul113
Thurmann, M., Janney, J.G.: The diagnostic importance of fibrillatory wave size. Circulation 25, 991–994 (1962)
Bollmann, A., Kanuru, N.K., McTeague, K.K., Walter, P.F., DeLurgio, D.B., Langberg, J.J.: Frequency analysis of human atrial fibrillation using the surface electrocardiogram and its response to ibutilide. American Journal of Cardiology 81(12), 1439–1445 (1998)
Langley, P., Stridh, M., Rieta, J.J., Sornmo, L., Millet-Roig, J., Murray, A.: Comparison of atrial rhythm extraction techniques for the estimation of the main atrial frequency from the 12-lead electrocardiogram in atrial fibrillation. In: Proc. Computers in Cardiology, pp. 29–32 (2002)
Welch, P.: The use of fast fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics 15(2), 70–73 (1967)
Hyvärinen, A., Oja, E.: Independent component analysis: algorithms and applications. Neural Networks 13(4-5), 411–430 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Donoso, F., Lecannelier, E., Pino, E., Rojas, A. (2011). Reliable Atrial Activity Extraction from ECG Atrial Fibrillation Signals. In: San Martin, C., Kim, SW. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2011. Lecture Notes in Computer Science, vol 7042. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25085-9_74
Download citation
DOI: https://doi.org/10.1007/978-3-642-25085-9_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25084-2
Online ISBN: 978-3-642-25085-9
eBook Packages: Computer ScienceComputer Science (R0)