Heart Beat Classification of ECGs Using Morphology and Beat Intervals

Author

Sadiq, Ismail ; Khan, Shoab Ahmad

Author_Institution

Coll. of Electr. & Mech. Eng., Nat. Univ. of Sci. & Technol., Rawalpindi, Pakistan

fYear

2011

fDate

10-12 May 2011

Firstpage

1

Lastpage

5

Abstract

The paper presents an automated approach to beat recognition of four different beat types in ECG´s, namely Normal beats, Ventricular ectopic beats, Supra-ventricular ectopic beats and Fusion beats. The feature vector used to differentiate between the different beats contains morphological features and beat intervals for each beat. The features include parameters like the pre- RR interval, post-RR interval, the peaks of the Q, R, S, T points, as well as the time duration between different fiducial points. The feature vector is then fed to a neuro fuzzy classifier which determines the type of heart beat.

Keywords

electrocardiography; feature extraction; fuzzy logic; medical signal processing; neurophysiology; signal classification; ECGs; automated approach; beat intervals; feature vector; fiducial points; fusion beats; heart beat classification; morphological features; neuro fuzzy classifier; post-RR interval; pre-RR interval; supraventricular ectopic beats; Classification algorithms; Electrocardiography; Heart beat; Heart rate variability; Morphology; Support vector machine classification; Tuning;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on

Conference_Location

Wuhan

ISSN

2151-7614

Print_ISBN

978-1-4244-5088-6

Type

conf

DOI

10.1109/icbbe.2011.5780248

Filename

5780248