Title
Automated Detection of Paroxysmal Atrial Fibrillation Using an Information-Based Similarity Approach.
Abstract
Atrial fibrillation (AF) is an abnormal rhythm of the heart, which can increase heart-related complications. Paroxysmal AF episodes occur intermittently with varying duration. Human-based diagnosis of paroxysmal AF with a longer-term electrocardiogram recording is time-consuming. Here we present a fully automated ensemble model for AF episode detection based on RR-interval time series, applying a novel approach of information-based similarity analysis and ensemble scheme. By mapping RR-interval time series to binary symbolic sequences and comparing the rank-frequency patterns of m-bit words, the dissimilarity between AF and normal sinus rhythms (NSR) were quantified. To achieve high detection specificity and sensitivity, and low variance, a weighted variation of bagging with multiple AF and NSR templates was applied. By performing dissimilarity comparisons between unknown RR-interval time series and multiple templates, paroxysmal AF episodes were detected. Based on our results, optimal AF detection parameters are symbolic word length m = 9 and observation window n = 150, achieving 97.04% sensitivity, 97.96% specificity, and 97.78% overall accuracy. Sensitivity, specificity, and overall accuracy vary little despite changes in m and n parameters. This study provides quantitative information to enhance the categorization of AF and normal cardiac rhythms.
Year
DOI
Venue
2017
10.3390/e19120677
ENTROPY
Keywords
Field
DocType
paroxysmal atrial fibrillation,RR-interval time series,symbolic sequence,information-based similarity index,ensemble model
Atrial fibrillation,Similarity analysis,Pattern recognition,Artificial intelligence,Paroxysmal atrial fibrillation,Statistics,Rhythm,Mathematics,Paroxysmal AF,Cardiac rhythms
Journal
Volume
Issue
ISSN
19
12
1099-4300
Citations 
PageRank 
References 
4
0.43
6
Authors
6
Name
Order
Citations
PageRank
Xing-Ran Cui1102.64
Emily Chang2101.33
Wen-Hung Yang340.43
Bernard C. Jiang47911.80
Albert C.-C. Yang5212.94
Chung-Kang Peng6295.02