DocumentCode :
2124932
Title :
Predicting the onset of paroxysmal atrial fibrillation: the Computers in Cardiology Challenge 2001
Author :
Moody, GB ; Goldberger, AL ; McClennen, S. ; Swiryn, SP
Author_Institution :
Div. of Health Sci. & Technol., Harvard-MIT, Cambridge, MA, USA
fYear :
2001
fDate :
2001
Firstpage :
113
Lastpage :
116
Abstract :
The advent of pacing techniques for preventing the onset of atrial arrhythmias motivates the development of accurate predictors of these arrhythmias, and of paroxysmal atrial fibrillation (PAF) in particular The goals of the second annual Computers in Cardiology Challenge were to determine if segments of ECG that do not include PAF contain information sufficient (1) to distinguish subjects at risk of PAF from others not at risk, and (2) to predict imminent PAF in at-risk subjects. Via PhysioNet, 18 teams of participants studied training and test databases containing two half-hour ECG recordings from each of 100 subjects (of whom 53 experienced PAF immediately following one of the two recordings). The results indicate that roughly 80% of the subjects can be correctly classified (as at-risk or not), and that imminent PAF can be predicted in roughly 80% of subjects at risk. The most successful approaches were based on analyses of the incidence of premature atrial complexes (PACs) and P-wave variability
Keywords :
electrocardiography; medical signal processing; prediction theory; signal classification; ECG recordings; ECG segments; P-wave variability; PhysioNet; at-risk subjects; cardiology computing; pacing techniques; paroxysmal atrial fibrillation onset prediction; remature atrial complexes; subject risk classification; test databases; training databases; Atrial fibrillation; Cardiology; Databases; Electrocardiography; Picture archiving and communication systems; Rhythm; Rough surfaces; Surface morphology; Surface roughness; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers in Cardiology 2001
Conference_Location :
Rotterdam
ISSN :
0276-6547
Print_ISBN :
0-7803-7266-2
Type :
conf
DOI :
10.1109/CIC.2001.977604
Filename :
977604
Link To Document :
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