학술논문

Quantitative Evaluation of Temporal Episode Patterns in Paroxysmal Atrial Fibrillation
Document Type
Conference
Source
2018 Computing in Cardiology Conference (CinC) Computing in Cardiology Conference (CinC), 2018. 45:1-4 Sep, 2018
Subject
Bioengineering
Computing and Processing
Signal Processing and Analysis
Monitoring
Databases
Atrial fibrillation
Biomedical engineering
Cardiology
Microsoft Windows
Biomedical measurement
Language
ISSN
2325-887X
Abstract
Flow velocity in left atrial appendage decreases when paroxysmal atrial fibrillation (PAF) progresses to longer episodes, suggesting that the temporal PAF episode pattern may be related to risk of thrombus formation. This study investigates the feasibility of discriminating episode patterns based on two descriptors: the aggregation characterizes the temporal distribution of PAF episodes, whereas the Gini coefficient characterizes differences in episode duration. The descriptors were studied on three PhysioNet databases with annotated PAF episodes, resulting in a total of 102 recordings. Three types of patterns were defined: congregation of several episodes in a single and multiple clusters, and episodes dispersed over the entire monitoring period. The results show that the aggregation descriptor achieves large values for patterns with a single and multiple clusters $(0.76\pm 0.07$ and $0.60\pm 0.08$, respectively). In contrast, much lower values are obtained for dispersed episode patterns $(0.10\pm 0.05)$. The Gini coefficient is better suited for discriminating among the patterns with high PAF burden and, therefore, represents a descriptor which is complementary to aggregation. Both descriptors may have relevance when studying the relationship between episode pattern and the risk of thrombus formation.