DocumentCode :
3562254
Title :
Altered nonlinear dynamics of atrial fibrillation detected after ablation
Author :
Sunderland, Kevin W. ; Berman, Adam E. ; Schumacher, Autumn M.
Author_Institution :
Georgia Regents Univ., Augusta, GA, USA
fYear :
2014
Firstpage :
809
Lastpage :
812
Abstract :
Atrial fibrillation (AF) consists of uncoordinated atrial and ventricular electrical activity. Quantifying the nonlinear dynamics of AF is difficult since the QRS wave masks the P wave patterns on the electrocardiogram (ECG). The purpose of this project was to minimize the size of the QRS wave and analyze the remaining atrial ECG signal to better measure the nonlinear dynamics underlying AF. A continuous single-lead ECG signal was digitally recorded during atrial myocardial tissue ablation in 19 adult AF patients. Thirty-second segments of AF were selected before and after ablation from each ECG recording. The ECG segments were processed with the adaptive singular value cancelation (ASVC) technique to reduce the size of the QRS wave. The remaining atrial signal was then analyzed with recurrence quantification analysis (RQA) to quantify its nonlinear dynamics. The RQA variable, %determinism, significantly decreased after ablation (p = .042). This finding suggests that the processed AF signal contained less structure in the nonlinear domain after ablation of the atrial myocardial tissue. These results demonstrated that the ASVC technique reduced the size of the QRS wave allowing RQA to detect alterations in the nonlinear dynamics of the remaining atrial ECG signal after ablation.
Keywords :
adaptive signal detection; adaptive signal processing; bioelectric phenomena; electrocardiography; medical signal processing; muscle; surgery; AF dynamics; AF nonlinear dynamics; AF patients; AF segments; AF signal structure; ASVC technique-based QRS wave size reduction; ECG P wave patterns; ECG Q wave; ECG R wave; ECG S wave; ECG recording; QRS wave size minimization; RQ analysis; RQA altered nonlinear dynamics detection; RQA variable; adaptive singular value cancelation technique; atrial ECG signal; atrial electrocardiogram signal; atrial fibrillation dynamics; atrial fibrillation patients; atrial fibrillation segments; atrial myocardial tissue ablation; atrial signal analysis; atrial-ventricular electrical activity; continuous single-lead ECG signal; electrocardiogram P wave patterns; electrocardiogram Q wave; electrocardiogram R wave; electrocardiogram S wave; electrocardiogram recording; nonlinear dynamics measurement; nonlinear dynamics quantification; recurrence quantification analysis; single-lead electrocardiogram signal; uncoordinated atrial electrical activity; uncoordinated ventricular electrical activity; Abstracts; Entropy; Heart; Market research; Myocardium; Physiology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing in Cardiology Conference (CinC), 2014
ISSN :
2325-8861
Print_ISBN :
978-1-4799-4346-3
Type :
conf
Filename :
7043166
Link To Document :
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