Signal Analysis in Atrial Fibrillation

Alcaraz, Raúl; Rieta, J.J.

doi:10.1007/978-981-10-5092-3_17

Cited by 2 publications

(1 citation statement)

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“…The f -waves are characterized by a time-varying morphology, presenting waveforms of different sizes, amplitude and timings [17]. However, in the last years the degree of organization of these waves has been strongly correlated with a successful result in different treatments of AF, such as electrical cardioversion and catheter ablation [18]. Thus, in the present work a novel algorithm to estimate time course of the f -waves organization is proposed to anticipate long-term outcome of SA.…”

Section: Time Variability Of the F -Waves Energymentioning

confidence: 99%

Time Variability of Fibrillatory Waves Energy Predicts Long-Term Outcome of Atrial Fibrillation Concomitant Surgical Ablation

Rodenas¹,

Escribano²,

Martinez-Iniesta³

et al. 2020

2020 Computing in Cardiology Conference (CinC)

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Surgical ablation (SA) is the most effective procedure to terminate atrial fibrillation (AF) in patients requiring concomitant open-heart surgery. However, considering the great stress provoked in the patient's heart, along with the benefits of anticipating antiarrhythmic therapeutical decisions, preoperative prediction of long-term failure of the procedure is an interesting clinical challenge. Hence, the present work introduces a novel algorithm to anticipate SA outcome after one year of follow-up by just analyzing the surface ECG. The method firstly extracts fibrillatory waves reflected on standard lead V1 using an adaptive QRST cancellation approach. The resulting signal is then segmented into 1 s-length intervals and wavelet energy is computed for all of them. Finally, the coefficient of variation of the time series obtained for the 7th scale is computed. Analyzing 20 second-length preoperative ECG excerpts from 53 persistent AF patients undergoing concomitant openheart surgery, only the proposed method reported statistically significant differences between the patients who relapsed to AF and those who maintained sinus rhythm during the follow-up. The algorithm also provided values of sensitivity, specificity, and accuracy between 10 and 20% better than the well-established dominant atrial frequency and fibrillatory waves amplitude, thus suggesting to be a promising predictor of AF recurrence after SA.

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Section: Time Variability Of the F -Waves Energymentioning

confidence: 99%