Detection of supraventricular and ventricular ectopic beats using a single lead ECG

Author

de Chazal, Philip

Author_Institution

Marcs Inst., Univ. of Western Sydney, Sydney, NSW, Australia

fYear

2013

fDate

3-7 July 2013

Firstpage

45

Lastpage

48

Abstract

Two simple algorithms for supraventricular (SVEB) and ventricular ectopic beat (VEB) detection using the electrocardiogram (ECG) are presented. Both algorithms use time-domain features and a linear classifier. The first algorithm requires QRS detection only and the second algorithm requires P, QRS and T wave segmentation. Data was obtained from the 44 non-pacemaker recordings of the MIT-BIH arrhythmia database and contained approximately 100,000 beats. Performance assessment of the best system resulted in an accuracy of 94.4% when discriminating SVEB from non-SVEBs and 97.8% in discriminating VEB from non-VEBs.

Keywords

electrocardiography; medical signal detection; medical signal processing; signal classification; time-domain analysis; MIT-BIH arrhythmia database; P wave segmentation; QRS detection; QRS wave segmentation; SVEB; T wave segmentation; electrocardiogram; linear classifier; nonpacemaker recordings; performance assessment; single lead ECG; supraventricular ectopic beat detection; time-domain features; ventricular ectopic beat detection; Databases; Electrocardiography; Feature extraction; Heart beat; Heart rate variability; Morphology; Pregnancy;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE

Conference_Location

Osaka

ISSN

1557-170X

Type

conf

DOI

10.1109/EMBC.2013.6609433

Filename

6609433