DocumentCode :
1966493
Title :
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
Link To Document :
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