ABSTRACT Dominant frequency (DF) of electrophysiological data is an effective approach to estimate the activation rate during Atrial Fibrillation (AF) and it is important to understand the pathophysiology of AF and to help select candidate sites for ablation. Frequency analysis is used to find and track DF. It is important to minimize the catheter insertion time in the atria as it contributes to the risk for the patients during this procedure, so DF estimation needs to be obtained as quickly as possible. A comparison of computation tim- es taken for spectrum estimation analysis is presented in this paper. Fast Fourier Transform (FFT), Blackman-Tukey (BT), Autoregressive (AR) and Multiple Signal Classification (MUSIC) methods are used to obtain the frequency spectrum of the signals. The time to produce DF was measured for each method. The method which takes the shortest time for analysis is selected for real time application purpose.
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nullAhmad, A. , Schlindwein, F. and Ng, G. (2010) Comparison of computation time for estimation of dominant frequency of atrial electrograms: Fast fourier transform, blackman tukey, autoregressive and multiple signal classification. Journal of Biomedical Science and Engineering, 3, 843-847. doi: 10.4236/jbise.2010.39114.
 Ng, J., Goldberger, J. J. (2007) Understanding and interpreting dominant frequency analysis of AF electrograms, Journal of Cardiovasc. Electrophysiol, 18(6), 680-685.
Woo, S.-C. and Goo, N.-S. (2007) Analysis of the bending fracture process for piezoelectric composite actuators using dominant frequency bands by acoustic emission. Composites Science and Technology, 67, 1499-1508.
Lindblom Bj?rn, Diehl Randy and Creeger Carl. (2009) Do ‘Dominant Frequencies’ explain the listener’s response to formant and spectrum shape variations? Speech Communication, 51(7), 622-629.
Berenfeld, O. (2007) Quantifying activation frequency in atrial fibrillation to establish underlying mechanisms and ablation guidance. Heart Rhythm, 4(9), 1225-1234.
Pappone, C., Rosanio, S., Augello, G., Gallus, G., Viced- omini, G., Mazzone, P., Gulletta, S., Gugliotta, F., Papp- one, A. and Santinelli, V. (2003) Mortality, morbidity, and quality of life after circumferential pulmonary vein ablation for atrial fibrillation: Outcomes from a control- ed nonrandomized long term study. Journal of American college of cardiology, 42(2), 185-197.
Jacquemet, V., Kappenberger, L. and Henriquez, C. S, (2008) Modeling atrial arrhythmias: Impact on clinical diagnosis and therapies. IEEE Reviews in Biomedical Engineering, 1, 94-144.
Gonska, B.D., Bauerle, H.J.and Japha, T. (2009) Atrial fibrillation ablation: Who comes into consideration? Her- zschrittmachertherapie und Elektrophysiologie, 20(2), 76-81.
Skanes, A.C., Mandapati, R., Berenfeld, O., Davidenko, J.M. and Jalife J. (1998) Spatiotemporal periodicity during atrial fibrillation in the isolated sheep heart. Circulation, 98(12), 1236-1248.
Mandapati, R., Skanes, A., Chen, J., Berenfeld, O. and Jalife, J. (2000) Stable microreentrant sources as a me- chanism of atrial fibrillation in the isolated sheep heart. Circulation, 101(2), 194-199.
Calkins, H., Brugada, J., Packer, D.L., Cappato, R., Chen, S.A. and Crijns, H.J. et al (2007). HRS/EHRA/ECAS expert consensus statement on catheter and surgical ablation of atrial fibrillation: Recommendations for personnel, policy, procedures and follow-up. Europace, 9(6), 335- 379.
Cappato, R., Calkins, H., Chen, S.A., Davies, W., Iesaka, Y., Kalman, J., Kim, Y.H, Klein, G., Packer, D. and Ska- nes, A. (2005) Worldwide survey on the methods, efficacy, and safety of catheter ablation for human atrial fibrillation. Circulation, 111(9), 1100-1105.
Prudente, L.A., Moorman, J.R., Lake, D., Xiao, Y., Greebaum, H., Mangrum, J.M., Dimarco, J.P. and Ferguson, J.D. (2009) Femoral vascular complications following catheter ablation of atrial fibrillation. Journal of Interventional Cardiac Electrophysiology, 26(1), 59-64.
Ifeachor Emmanuel, C. and Jervis Barrie, W. (2002) Digital signal processing:A practical approach. 2nd Edition, Prentice Hall, New Jersey.
Welch Peter, D. (1967) The use of fast fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transcations on Audio and Electroacoustics, 15(2), 70- 73.
Kay Steven, M. (1988) Modern spectral estimation theory & application. Prentice Hall, New Jersey.
Beauchamp, K. and Yuen C. (1979) Digital methods for signal analysis. George Allen & Unwin, London.
Schmidt R. (1979) Multiple emitter location and signal parameter estimation. Proceedings of RADC spectrum estimation workshop, Saxpy Computer Corporation, USA, 243-258.
Vaseghi Saeed, V. (2008) Advanced digital signal processing and noise reduction, 3rd Edition, Wiley, Chichester.
Hayes Monson, H. (1996) Statistical digital signal processing and modeling. John Wiley & Son, Chichester.
Pisarenko, V.F. (1973) The retrieval of harmonics from a covariance function. Geophysical Journal Royal Astronomical Society, 33(3), 347-366.