Literature DB >> 16442328

Predicting spontaneous termination of atrial fibrillation using the surface ECG.

Frida Nilsson1, Martin Stridh, Andreas Bollmann, Leif Sörnmo.   

Abstract

By recognizing and characterizing conditions under which atrial fibrillation (AF) is likely to terminate spontaneously or be sustained, improved treatment of sustained AF may result and unnecessary treatment of self-terminating AF avoided. Time-frequency measures that characterize AF, such as fibrillatory frequency, amplitude, and waveform shape (exponential decay), are extracted from the residual ECG following QRST cancellation. Three complexity measures are also studied, characterizing the degree of organization of atrial activity. All measures are analysed using a training set, consisting of 20 recordings of AF with known termination properties, and a test set of 30 recordings. Spontaneous termination was best predicted by a low and stable fibrillatory frequency and a low exponential decay. Using these predictors, 90% of the test set was correctly classified into terminating and sustained AF. Neither fibrillation amplitude nor the complexity measures differed significantly between the two sets.

Entities:  

Mesh:

Year:  2006        PMID: 16442328     DOI: 10.1016/j.medengphy.2005.11.010

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  11 in total

1.  Right atrial organization and wavefront analysis in atrial fibrillation.

Authors:  Ulrike Richter; Andreas Bollmann; Daniela Husser; Martin Stridh
Journal:  Med Biol Eng Comput       Date:  2009-10-15       Impact factor: 2.602

2.  Association between atrial fibrillatory rate and heart rate variability in patients with atrial fibrillation and congestive heart failure.

Authors:  Valentina D A Corino; Iwona Cygankiewicz; Luca T Mainardi; Martin Stridh; Rafael Vasquez; Antonio Bayes de Luna; Fredrik Holmqvist; Wojciech Zareba; Pyotr G Platonov
Journal:  Ann Noninvasive Electrocardiol       Date:  2012-11-22       Impact factor: 1.468

3.  A non-invasive method to predict electrical cardioversion outcome of persistent atrial fibrillation.

Authors:  Raúl Alcaraz; José Joaquín Rieta
Journal:  Med Biol Eng Comput       Date:  2008-04-24       Impact factor: 2.602

4.  Non-invasive atrial fibrillation organization follow-up under successive attempts of electrical cardioversion.

Authors:  Raúl Alcaraz; José Joaquín Rieta; Fernando Hornero
Journal:  Med Biol Eng Comput       Date:  2009-12       Impact factor: 2.602

5.  Predicting termination of paroxysmal atrial fibrillation using empirical mode decomposition of the atrial activity and statistical features of the heart rate variability.

Authors:  Maryam Mohebbi; Hassan Ghassemian
Journal:  Med Biol Eng Comput       Date:  2014-03-06       Impact factor: 2.602

6.  Long-term characterization of persistent atrial fibrillation: wave morphology, frequency, and irregularity analysis.

Authors:  Rebeca Goya-Esteban; Frida Sandberg; Óscar Barquero-Pérez; Arcadio García-Alberola; Leif Sörnmo; José Luis Rojo-Álvarez
Journal:  Med Biol Eng Comput       Date:  2014-10-05       Impact factor: 2.602

7.  Autonomic modulation before and after paroxysmal atrial fibrillation events in patients with ischemic heart disease.

Authors:  Ting-Wei Ernie Liao; Li-Wei Lo; Yenn-Jiang Lin; Shih-Lin Chang; Yu-Feng Hu; Cheng-I Wu; Fa-Po Chung; Tze-Fan Chao; Jo-Nan Liao; Shih-Ann Chen
Journal:  Ann Noninvasive Electrocardiol       Date:  2020-05-26       Impact factor: 1.468

8.  Central tendency measure and wavelet transform combined in the non-invasive analysis of atrial fibrillation recordings.

Authors:  Raúl Alcaraz; José Joaquín Rieta
Journal:  Biomed Eng Online       Date:  2012-08-09       Impact factor: 2.819

9.  Application of Wavelet Entropy to predict atrial fibrillation progression from the surface ECG.

Authors:  Raúl Alcaraz; José J Rieta
Journal:  Comput Math Methods Med       Date:  2012-09-26       Impact factor: 2.238

10.  Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization.

Authors:  Hung-Chih Chiu; Yen-Hung Lin; Men-Tzung Lo; Sung-Chun Tang; Tzung-Dau Wang; Hung-Chun Lu; Yi-Lwun Ho; Hsi-Pin Ma; Chung-Kang Peng
Journal:  Sci Rep       Date:  2015-08-19       Impact factor: 4.379

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