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168 related items for PubMed ID: 12549732

  • 1. A method for quantifying atrial fibrillation organization based on wave-morphology similarity.
    Faes L, Nollo G, Antolini R, Gaita F, Ravelli F.
    IEEE Trans Biomed Eng; 2002 Dec; 49(12 Pt 2):1504-13. PubMed ID: 12549732
    [Abstract] [Full Text] [Related]

  • 2. Quantification of synchronization during atrial fibrillation by Shannon entropy: validation in patients and computer model of atrial arrhythmias.
    Masè M, Faes L, Antolini R, Scaglione M, Ravelli F.
    Physiol Meas; 2005 Dec; 26(6):911-23. PubMed ID: 16311441
    [Abstract] [Full Text] [Related]

  • 3. An automatic system for the analysis and classification of human atrial fibrillation patterns from intracardiac electrograms.
    Nollo G, Marconcini M, Faes L, Bovolo F, Ravelli F, Bruzzone L.
    IEEE Trans Biomed Eng; 2008 Sep; 55(9):2275-85. PubMed ID: 18713697
    [Abstract] [Full Text] [Related]

  • 4. Dynamic time warping applied to estimate atrial fibrillation temporal organization from the surface electrocardiogram.
    Alcaraz R, Hornero F, Rieta JJ.
    Med Eng Phys; 2013 Sep; 35(9):1341-8. PubMed ID: 23566715
    [Abstract] [Full Text] [Related]

  • 5. Short-time regularity assessment of fibrillatory waves from the surface ECG in atrial fibrillation.
    Alcaraz R, Hornero F, Martínez A, Rieta JJ.
    Physiol Meas; 2012 Jun; 33(6):969-84. PubMed ID: 22561133
    [Abstract] [Full Text] [Related]

  • 6. A new approach to automated assessment of fractionation of endocardial electrograms during atrial fibrillation.
    Kremen V, Lhotská L, Macas M, Cihák R, Vancura V, Kautzner J, Wichterle D.
    Physiol Meas; 2008 Dec; 29(12):1371-81. PubMed ID: 18946155
    [Abstract] [Full Text] [Related]

  • 7. The application of nonlinear metrics to assess organization differences in short recordings of paroxysmal and persistent atrial fibrillation.
    Alcaraz R, Rieta JJ.
    Physiol Meas; 2010 Jan; 31(1):115-30. PubMed ID: 19946175
    [Abstract] [Full Text] [Related]

  • 8. Long- and short-term temporal stability of complex fractionated atrial electrograms in human left atrium during atrial fibrillation.
    Scherr D, Dalal D, Cheema A, Nazarian S, Almasry I, Bilchick K, Cheng A, Henrikson CA, Spragg D, Marine JE, Berger RD, Calkins H, Dong J.
    J Cardiovasc Electrophysiol; 2009 Jan; 20(1):13-21. PubMed ID: 18775047
    [Abstract] [Full Text] [Related]

  • 9. Sequential characterization of atrial tachyarrhythmias based on ECG time-frequency analysis.
    Stridh M, Sörnmo L, Meurling CJ, Olsson SB.
    IEEE Trans Biomed Eng; 2004 Jan; 51(1):100-14. PubMed ID: 14723499
    [Abstract] [Full Text] [Related]

  • 10. Improvements in atrial fibrillation detection for real-time monitoring.
    Babaeizadeh S, Gregg RE, Helfenbein ED, Lindauer JM, Zhou SH.
    J Electrocardiol; 2009 Jan; 42(6):522-6. PubMed ID: 19608194
    [Abstract] [Full Text] [Related]

  • 11. P-wave morphology assessment by a gaussian functions-based model in atrial fibrillation patients.
    Censi F, Calcagnini G, Ricci C, Ricci RP, Santini M, Grammatico A, Bartolini P.
    IEEE Trans Biomed Eng; 2007 Apr; 54(4):663-72. PubMed ID: 17405373
    [Abstract] [Full Text] [Related]

  • 12. Frequency tracking of atrial fibrillation using hidden Markov models.
    Sandberg F, Stridh M, Sörnmo L.
    IEEE Trans Biomed Eng; 2008 Feb; 55(2 Pt 1):502-11. PubMed ID: 18269985
    [Abstract] [Full Text] [Related]

  • 13. Wavelet bidomain sample entropy analysis to predict spontaneous termination of atrial fibrillation.
    Alcaraz R, Rieta JJ.
    Physiol Meas; 2008 Jan; 29(1):65-80. PubMed ID: 18175860
    [Abstract] [Full Text] [Related]

  • 14. Surface ECG organization analysis to predict paroxysmal atrial fibrillation termination.
    Alcaraz R, Rieta JJ.
    Comput Biol Med; 2009 Aug; 39(8):697-706. PubMed ID: 19523611
    [Abstract] [Full Text] [Related]

  • 15. Classification of electrocardiographic P-wave morphology.
    Carlson J, Johansson R, Olsson SB.
    IEEE Trans Biomed Eng; 2001 Apr; 48(4):401-5. PubMed ID: 11322527
    [Abstract] [Full Text] [Related]

  • 16. Predicting spontaneous termination of atrial fibrillation using the surface ECG.
    Nilsson F, Stridh M, Bollmann A, Sörnmo L.
    Med Eng Phys; 2006 Oct; 28(8):802-8. PubMed ID: 16442328
    [Abstract] [Full Text] [Related]

  • 17. Form analysis using digital signal processing reliably discriminates far-field R waves from P waves.
    Van Hemel NM, Wohlgemuth P, Engbers JG, Lawo T, Nebaznivy J, Taborsky M, Witte J, Boute W, Munneke D, Van Groeningen C.
    Pacing Clin Electrophysiol; 2004 Dec; 27(12):1615-24. PubMed ID: 15613124
    [Abstract] [Full Text] [Related]

  • 18. Predicting termination of atrial fibrillation based on the structure and quantification of the recurrence plot.
    Sun R, Wang Y.
    Med Eng Phys; 2008 Nov; 30(9):1105-11. PubMed ID: 18343707
    [Abstract] [Full Text] [Related]

  • 19. Analysis of fractionated atrial fibrillation electrograms by wavelet decomposition.
    Houben RP, de Groot NM, Allessie MA.
    IEEE Trans Biomed Eng; 2010 Jun; 57(6):1388-98. PubMed ID: 20142151
    [Abstract] [Full Text] [Related]

  • 20. [Study of hybrid time-frequency method and characterization of atrial fibrillation from surface ECG].
    Huang Z, Zhao Y.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2008 Dec; 25(6):1254-9. PubMed ID: 19166187
    [Abstract] [Full Text] [Related]

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