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

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

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

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

Biomedical Engineering & Biotechnology

Aristotle University of Thessaloniki

Research output: Contribution to journal › Conference article › peer-review

18 Scopus citations

Abstract

A new way of detecting R-wave in QRS complex of electrocardiogram (ECG) based on higher-order statistics (HOS) is presented in this paper. The proposed method employs HOS-based parameters, such as skewness and kurtosis, in order to formulate an adaptive detector of 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.

Original language	British English
Pages (from-to)	344-347
Number of pages	4
Journal	Annual Reports of the Research Reactor Institute, Kyoto University
Volume	1
State	Published - 2001
Event	23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey Duration: 25 Oct 2001 → 28 Oct 2001

Keywords

Adaptive robust detector
Heart rate screening
Kurtosis
Massachusetts Institute of Technology/Beth Israel Hospital (MIT/BIH) ECG database
QRS complex
Skewness

Cite this

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title = "Enhancement of R-wave detection in ECG data analysis using higher-order statistics",

abstract = "A new way of detecting R-wave in QRS complex of electrocardiogram (ECG) based on higher-order statistics (HOS) is presented in this paper. The proposed method employs HOS-based parameters, such as skewness and kurtosis, in order to formulate an adaptive detector of 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 robust detector, Heart rate screening, Kurtosis, Massachusetts Institute of Technology/Beth Israel Hospital (MIT/BIH) ECG database, QRS complex, Skewness",

author = "Panoulas, {Kostas I.} and Hadjileontiadis, {Leontios J.} and Panas, {Stavros M.}",

year = "2001",

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volume = "1",

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journal = "Annual Reports of the Research Reactor Institute, Kyoto University",

issn = "0454-9244",

note = "23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society ; Conference date: 25-10-2001 Through 28-10-2001",

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TY - JOUR

T1 - Enhancement of R-wave detection in ECG data analysis using higher-order statistics

AU - Panoulas, Kostas I.

AU - Hadjileontiadis, Leontios J.

AU - Panas, Stavros M.

PY - 2001

Y1 - 2001

N2 - A new way of detecting R-wave in QRS complex of electrocardiogram (ECG) based on higher-order statistics (HOS) is presented in this paper. The proposed method employs HOS-based parameters, such as skewness and kurtosis, in order to formulate an adaptive detector of 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.

AB - A new way of detecting R-wave in QRS complex of electrocardiogram (ECG) based on higher-order statistics (HOS) is presented in this paper. The proposed method employs HOS-based parameters, such as skewness and kurtosis, in order to formulate an adaptive detector of 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.

KW - Adaptive robust detector

KW - Heart rate screening

KW - Kurtosis

KW - Massachusetts Institute of Technology/Beth Israel Hospital (MIT/BIH) ECG database

KW - QRS complex

KW - Skewness

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M3 - Conference article

AN - SCOPUS:0035782323

SN - 0454-9244

VL - 1

SP - 344

EP - 347

JO - Annual Reports of the Research Reactor Institute, Kyoto University

JF - Annual Reports of the Research Reactor Institute, Kyoto University

T2 - 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 25 October 2001 through 28 October 2001

ER -

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

Abstract

Keywords

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