Paper Info
Title
Detection Of Atrial Fibrillation Using Model-Based Ecg Analysis
Abstract
Atrial Fibrillation (AF) is an arrhythmia that can lead to several patient risks. This kind of arrhythmia affects mostly elderly people, in particular those who suffer from heart failure (one of the main causes of hospitalization). Thus, detection of AF becomes decisive in the prevention of cardiac threats. In this paper an algorithm for A F detection based on a novel algorithm architecture and feature extraction methods is proposed. The aforementioned architecture is based on the analysis of the three main physiological characteristics of AF: i) P wave absence ii) heart rate irregularity and iii) atrial activity (AA). Discriminative features are extracted using model-based statistic and frequency based approaches. Sensitivity and specificity results (respectively, 93.80% and 96.09% using the MIT-BIH AF database) show that the proposed algorithm is able to outperform state-of-the-art methods.
Year
DOI
Venue
2008
10.1109/ICPR.2008.4761755
19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6
Keywords
Field
DocType
classification algorithms,feature extraction,cardiology,probabilistic logic,statistical analysis,algorithm design and analysis,geriatrics
Atrial fibrillation,Heart failure,Algorithm design,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Heart rate,Electrocardiography,Statistical classification,Discriminative model
Conference
ISSN
Citations 
PageRank 
1051-4651
16
2.82
References 
Authors
0
6
Name
Order
Citations
PageRank
Ricardo Couceiro13510.16
Paulo Carvalho225047.68
Jorge Henriques36313.77
Manuel Antunes4449.87
Matthew Harris5608.45
Jorg Habetha64617.28