Enhancement of R-wave detection in ECG data analysis using higher-order statistics

Author

Panoulas, Kostas I. ; Hadjileontiadis, Leontios J. ; Panas, Stavros M.

Author_Institution

Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Greece

Volume

1

fYear

2001

fDate

2001

Firstpage

344

Abstract

A new way of detecting the R-wave in a QRS complex of an electrocardiogram (ECG) based on higher-order statistics (HOS) is presented. The proposed method employs HOS-based parameters, such as skewness and kurtosis, in order to formulate an adaptive detector of the R peak with high accuracy. Experimental results, when applying the proposed method to pre-classified ECG data from the Massachusetts Institute of Technology/Beth Israel Hospital (MIT/BIH) ECG database, prove that the proposed method exhibits over 99% of detectability, even when the ECG data are contaminated with noise. Due to its simplicity it could be feasible in a real-time context and it could be applied in routine ambulatory and/or clinical heart rate screening.

Keywords

adaptive signal detection; electrocardiography; higher order statistics; medical signal detection; medical signal processing; ECG data analysis; MIT/BIH ECG database; Massachusetts Institute of Technology/Beth Israel Hospital; QRS complex; R-wave detection enhancement; adaptive detector; clinical heart rate screening; electrocardiogram; high accuracy; higher-order statistics; kurtosis; noise; pre-classified ECG data; real-time context; routine ambulatory screening; simplicity; skewness; Cardiology; Data analysis; Databases; Detectors; Electrocardiography; Heart rate; Higher order statistics; Hospitals; Morphology; Signal analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7211-5

Type

conf

DOI

10.1109/IEMBS.2001.1018930

Filename

1018930