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A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds

Elgendi, Mohamed Y., Mahalingam, S., Jonkman, Mirjam E. and De Boer, Friso G. (2008). A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds. In: CSA2008. International Symposium on Computer Science and its Applications CSA2008, Hobart, 13-15 October, 2008.

Document type: Conference Paper

IRMA ID 77514990xPUB3
Author Elgendi, Mohamed Y.
Mahalingam, S.
Jonkman, Mirjam E.
De Boer, Friso G.
Title A Robust QRS Complex Detection Algorithm Using Dynamic Thresholds
Conference Name CSA2008. International Symposium on Computer Science and its Applications CSA2008
Conference Location Hobart
Conference Dates 13-15 October, 2008
Conference Publication Title Proceedings - International Symposium on Computer Science and Its Applications, CSA 2008
Place of Publication Hobart
Publisher IEEE
Publication Year 2008
ISBN 9780769534282   (check CDU catalogue  open catalogue search in new window)
Start Page 153
End Page 158
Total Pages 6
HERDC Category E1 - Conference Publication (DEST)
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.
 
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Created: Wed, 22 Apr 2009, 11:49:00 CST by Sarena Wegener