A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds

Mohamed Elgendi; Sivaram Mahalingam; Mirjam Jonkman; Friso De Boer

A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds

Mohamed Elgendi, Sivaram Mahalingam, Mirjam Jonkman, Friso De Boer

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review

Abstract

Automatic QRS Complex detection is important in ECG signal analysis. QRS detection methods are affected by the quality of the ECG recordings and the abnormalities in the ECG signals. In this paper, a generic algorithm is introduced to improve the detection of QRS complexes in Arrhythmia ECG Signals that suffer from: 1) non-stationary effects, 2) low signal-to-noise ratio, 3) negative QRS polarities, 4) low QRS amplitudes, and 5) ventricular ectopics. We compared the algorithm to the method described by Chouhan et al. [16] by applying both algorithms to 19 records of the MIT-BIH database. It was shown that the new algorithm achieves significantly better detection rates resulting in an overall 97.5% sensitivity and 99.9% positive predictivity. � 2008 IEEE.

Original language	English
Title of host publication	Proceedings - International Symposium on Computer Science and Its Applications, CSA 2008
Place of Publication	Hobart
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	-
Number of pages	6
Publication status	Published - 2008
Event	CSA2008. International Symposium on Computer Science and its Applications CSA2008 - Hobart Duration: 13 Oct 2008 → 15 Oct 2008

Conference

Conference	CSA2008. International Symposium on Computer Science and its Applications CSA2008
Period	13/10/08 → 15/10/08

Cite this

@inproceedings{5a23a99a71b9442092b4d117ad67bfaf,

title = "A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds",

abstract = "Automatic QRS Complex detection is important in ECG signal analysis. QRS detection methods are affected by the quality of the ECG recordings and the abnormalities in the ECG signals. In this paper, a generic algorithm is introduced to improve the detection of QRS complexes in Arrhythmia ECG Signals that suffer from: 1) non-stationary effects, 2) low signal-to-noise ratio, 3) negative QRS polarities, 4) low QRS amplitudes, and 5) ventricular ectopics. We compared the algorithm to the method described by Chouhan et al. [16] by applying both algorithms to 19 records of the MIT-BIH database. It was shown that the new algorithm achieves significantly better detection rates resulting in an overall 97.5% sensitivity and 99.9% positive predictivity. � 2008 IEEE.",

keywords = "Chemical shift, Complexation, Computer science, Computers, Electric currents, Electrocardiography, Electrochromic devices, Magnetic anisotropy, Signal analysis, Signal detection, Signal processing, Signal to noise ratio, Detection rates, Dynamic thresholds, ECG recordings, ECG signals, Generic algorithms, Mit-bih databases, New algorithms, Predictivity, QRS complex detections, QRS complexes, Qrs detections, Signal-to-Noise ratios, Algorithms",

author = "Mohamed Elgendi and Sivaram Mahalingam and Mirjam Jonkman and {De Boer}, Friso",

year = "2008",

language = "English",

pages = "--",

booktitle = "Proceedings - International Symposium on Computer Science and Its Applications, CSA 2008",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "CSA2008. International Symposium on Computer Science and its Applications CSA2008 ; Conference date: 13-10-2008 Through 15-10-2008",

}

Elgendi, M, Mahalingam, S, Jonkman, M & De Boer, F 2008, A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds. in Proceedings - International Symposium on Computer Science and Its Applications, CSA 2008. IEEE, Institute of Electrical and Electronics Engineers, Hobart, pp. -, CSA2008. International Symposium on Computer Science and its Applications CSA2008, 13/10/08.

A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds. / Elgendi, Mohamed; Mahalingam, Sivaram; Jonkman, Mirjam et al.
Proceedings - International Symposium on Computer Science and Its Applications, CSA 2008. Hobart: IEEE, Institute of Electrical and Electronics Engineers, 2008. p. -.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review

TY - GEN

T1 - A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds

AU - Elgendi, Mohamed

AU - Mahalingam, Sivaram

AU - Jonkman, Mirjam

AU - De Boer, Friso

PY - 2008

Y1 - 2008

N2 - Automatic QRS Complex detection is important in ECG signal analysis. QRS detection methods are affected by the quality of the ECG recordings and the abnormalities in the ECG signals. In this paper, a generic algorithm is introduced to improve the detection of QRS complexes in Arrhythmia ECG Signals that suffer from: 1) non-stationary effects, 2) low signal-to-noise ratio, 3) negative QRS polarities, 4) low QRS amplitudes, and 5) ventricular ectopics. We compared the algorithm to the method described by Chouhan et al. [16] by applying both algorithms to 19 records of the MIT-BIH database. It was shown that the new algorithm achieves significantly better detection rates resulting in an overall 97.5% sensitivity and 99.9% positive predictivity. � 2008 IEEE.

AB - Automatic QRS Complex detection is important in ECG signal analysis. QRS detection methods are affected by the quality of the ECG recordings and the abnormalities in the ECG signals. In this paper, a generic algorithm is introduced to improve the detection of QRS complexes in Arrhythmia ECG Signals that suffer from: 1) non-stationary effects, 2) low signal-to-noise ratio, 3) negative QRS polarities, 4) low QRS amplitudes, and 5) ventricular ectopics. We compared the algorithm to the method described by Chouhan et al. [16] by applying both algorithms to 19 records of the MIT-BIH database. It was shown that the new algorithm achieves significantly better detection rates resulting in an overall 97.5% sensitivity and 99.9% positive predictivity. � 2008 IEEE.

KW - Chemical shift

KW - Complexation

KW - Computer science

KW - Computers

KW - Electric currents

KW - Electrocardiography

KW - Electrochromic devices

KW - Magnetic anisotropy

KW - Signal analysis

KW - Signal detection

KW - Signal processing

KW - Signal to noise ratio

KW - Detection rates

KW - Dynamic thresholds

KW - ECG recordings

KW - ECG signals

KW - Generic algorithms

KW - Mit-bih databases

KW - New algorithms

KW - Predictivity

KW - QRS complex detections

KW - QRS complexes

KW - Qrs detections

KW - Signal-to-Noise ratios

KW - Algorithms

M3 - Conference Paper published in Proceedings

SP - -

BT - Proceedings - International Symposium on Computer Science and Its Applications, CSA 2008

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Hobart

T2 - CSA2008. International Symposium on Computer Science and its Applications CSA2008

Y2 - 13 October 2008 through 15 October 2008

ER -

A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds

Abstract

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