Automated Detection of Paroxysmal Atrial Fibrillation from Inter-Heartbeat Intervals

Author

Shouldice, R.B. ; Heneghan, C. ; de Chazal, P.

Author_Institution

Univ. Coll. Dublin, Dublin

fYear

2007

fDate

22-26 Aug. 2007

Firstpage

686

Lastpage

689

Abstract

An automated method for detecting episodes of probable paroxysmal atrial fibrillation based on processing blocks of inter-heartbeat intervals is considered. The method has very low computational requirements making it well-suited to near real-time, low power applications. A supervised linear discriminant classifier is used to estimate the likelihood of a block of inter-heartbeat intervals containing paroxysmal atrial fibrillation (PAF). Per block accuracies in separating normal from PAF were 92%, 94%, 100% and 100% when the method was used to process the Physionet MITDB, AFDB, NSRDB and NSR2DB databases respectively.

Keywords

cardiology; diseases; medical signal detection; inter-heartbeat intervals; linear discriminant classifier; paroxysmal atrial fibrillation; Adaptive filters; Aging; Atrial fibrillation; Band pass filters; Databases; Electrocardiography; Frequency; Heart beat; Histograms; Morphology; Atrial Fibrillation; Automatic Data Processing; Databases, Factual; Electrocardiography; Female; Humans; Male; Models, Cardiovascular;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE

Conference_Location

Lyon

ISSN

1557-170X

Print_ISBN

978-1-4244-0787-3

Type

conf

DOI

10.1109/IEMBS.2007.4352383

Filename

4352383