These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
138 related articles for article (PubMed ID: 24642478)
21. Time and frequency series combination for non-invasive regularity analysis of atrial fibrillation. Vayá C; Rieta JJ Med Biol Eng Comput; 2009 Jul; 47(7):687-96. PubMed ID: 19468772 [TBL] [Abstract][Full Text] [Related]
22. Enhancement of atrial fibrillation electrical cardioversion procedures through the arrhythmia organization estimation from the ECG. Alcaraz R; Hornero F; Rieta JJ Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():122-5. PubMed ID: 21096522 [TBL] [Abstract][Full Text] [Related]
23. Application of frequency and sample entropy to discriminate long-term recordings of paroxysmal and persistent atrial fibrillation. Alcaraz R; Sandberg F; Sörnmo L; Rieta JJ Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():4558-61. PubMed ID: 21096222 [TBL] [Abstract][Full Text] [Related]
24. Alteration of the P-wave non-linear dynamics near the onset of paroxysmal atrial fibrillation. Martínez A; Abásolo D; Alcaraz R; Rieta JJ Med Eng Phys; 2015 Jul; 37(7):692-7. PubMed ID: 25956053 [TBL] [Abstract][Full Text] [Related]
25. An echo state neural network for QRST cancellation during atrial fibrillation. Petrėnas A; Marozas V; Sörnmo L; Lukosevicius A IEEE Trans Biomed Eng; 2012 Oct; 59(10):2950-7. PubMed ID: 22929362 [TBL] [Abstract][Full Text] [Related]
26. Measures of spatiotemporal organization differentiate persistent from long-standing atrial fibrillation. Uldry L; Van Zaen J; Prudat Y; Kappenberger L; Vesin JM Europace; 2012 Aug; 14(8):1125-31. PubMed ID: 22308083 [TBL] [Abstract][Full Text] [Related]
27. Non-invasive organization variation assessment in the onset and termination of paroxysmal atrial fibrillation. Alcaraz R; Rieta JJ Comput Methods Programs Biomed; 2009 Feb; 93(2):148-54. PubMed ID: 18950894 [TBL] [Abstract][Full Text] [Related]
28. A non-invasive method to predict electrical cardioversion outcome of persistent atrial fibrillation. Alcaraz R; Rieta JJ Med Biol Eng Comput; 2008 Jul; 46(7):625-35. PubMed ID: 18437440 [TBL] [Abstract][Full Text] [Related]
29. Phase-rectified signal averaging used to estimate the dominant frequencies in ECG signals during atrial fibrillation. Lemay M; Prudat Y; Jacquemet V; Vesin JM IEEE Trans Biomed Eng; 2008 Nov; 55(11):2538-47. PubMed ID: 18990623 [TBL] [Abstract][Full Text] [Related]
30. A novel framework for noninvasive analysis of short-term atrial activity dynamics during persistent atrial fibrillation. Bonizzi P; Meste O; Zeemering S; Karel J; Lankveld T; Crijns H; Schotten U; Peeters R Med Biol Eng Comput; 2020 Sep; 58(9):1933-1945. PubMed ID: 32535735 [TBL] [Abstract][Full Text] [Related]
31. Noninvasive estimation of organization in atrial fibrillation as a predictor of sinus rhythm maintenance. Petersson R; Sandberg F; Platonov PG; Holmqvist F J Electrocardiol; 2011; 44(2):171-5. PubMed ID: 21168150 [TBL] [Abstract][Full Text] [Related]
32. Prediction of paroxysmal atrial fibrillation using nonlinear analysis of the R-R interval dynamics before the spontaneous onset of atrial fibrillation. Shin DG; Yoo CS; Yi SH; Bae JH; Kim YJ; Park JS; Hong GR Circ J; 2006 Jan; 70(1):94-9. PubMed ID: 16377931 [TBL] [Abstract][Full Text] [Related]
33. Wavelet bidomain regularity analysis to predict spontaneous termination of atrial fibrillation. Alcaraz R; Rieta JJ Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():1838-41. PubMed ID: 18002338 [TBL] [Abstract][Full Text] [Related]
35. [Approximate entropy of electrocardiogram signals in atrial fibrillation]. Horie T Rinsho Byori; 2013 Oct; 61(10):893-9. PubMed ID: 24371993 [TBL] [Abstract][Full Text] [Related]
36. Development of a toolbox for electrocardiogram-based interpretation of atrial fibrillation. Abächerli R; Leber R; Lemay M; Vesin JM; van Oosterom A; Schmid HJ; Kappenberger L J Electrocardiol; 2009; 42(6):517-21. PubMed ID: 19698953 [TBL] [Abstract][Full Text] [Related]
37. An algorithm to measure beat-to-beat cycle lengths for assessment of atrial electrogram rate and regularity during atrial fibrillation. Lee S; Ryu K; Waldo AL; Khrestian CM; Durand DM; Sahadevan J J Cardiovasc Electrophysiol; 2013 Feb; 24(2):199-206. PubMed ID: 23140386 [TBL] [Abstract][Full Text] [Related]
38. Application of Wavelet Entropy to predict atrial fibrillation progression from the surface ECG. Alcaraz R; Rieta JJ Comput Math Methods Med; 2012; 2012():245213. PubMed ID: 23056146 [TBL] [Abstract][Full Text] [Related]
39. Time and frequency recurrence analysis of persistent atrial fibrillation after electrical cardioversion. Alcaraz R; Rieta JJ Physiol Meas; 2009 May; 30(5):479-89. PubMed ID: 19369714 [TBL] [Abstract][Full Text] [Related]
40. Application of Hurst exponents to assess atrial reverse remodeling in paroxysmal atrial fibrillation. Julián M; Alcaraz R; Rieta JJ Physiol Meas; 2015 Nov; 36(11):2231-46. PubMed ID: 26393825 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]