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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/7113
Title: ANN-based QRS-complex analysis of ECG
Authors: Vijaya G.
Kumar V.
Verma H.K.
Published in: Journal of Medical Engineering and Technology
Abstract: Reliable detection of the QRS complex in either a normal or an abnormal ECG and its analysis is the first and foremost task in almost every ECG signal analysis system aimed at the diagnostic interpretation of ECG. Conventionally, detection of the QRS complex is accomplished using a rule-based/algorithmic approach. This work, uses the learn and generalize approach of an artificial neural network (ANN) for the detection of QRS complexes in either a normal or an abnormal ECG. This is followed by the analysis of the QRS complex to designate and measure the morphological components within the QRS complex in all 12 standard leads. An ANN has been developed to detect the QRS complex in ECG and trained, with the help of back propagation algorithm, on more than a hundred ECGs selected from the CSE Data Set-3. The trained ANN was tested on all the recordings of the CSE Data Set-3 and the sensitivity has been found to be 99.11%. Subsequent to the identification of the QRS complex, an analysis of this complex and measurement of peak amplitudes of the component waves is done. The results are validated using the CSE multi-lead measurement results. Both the QRS detection and the QRS analysis software developed in C-language have been successfully implemented on a PC-AT. The results are found to be in agreement with visual measurements carried out by medical experts.Reliable detection of the QRS complex in either a normal or an abnormal ECG and its analysis is the first and foremost task in almost every ECG signal analysis system aimed at the diagnostic interpretation of ECG. Conventionally, detection of the QRS complex is accomplished using a rule- based/algorithmic approach. This work, uses learn and generalize approach of an artificial neural network (ANN) for the detection of QRS complexes in either a normal or an abnormal ECG. This is followed by the analysis of the QRS complex to designate and measure the morphological components within the QRS complex in all 12 standard leads. An ANN has been developed to detect the QRS complex in ECG and trained, with the help of back propagation algorithm, on more than a hundred ECGs selected from the CSE Data Set-3. The trained ANN was tested on all the recordings of the CSE Data Set-3 and the sensitivity has been found to be 99.11%. Subsequent to the identification of the QRS complex, an analysis of this complex and measurement of peak amplitudes of the component waves is done. The results are validated using the CSE multi- lead measurement results. Both the QRS detection and the QRS analysis software developed in C-language have been successfully implemented on a PC- AT. The results are found to be in agreement with visual measurements carried out by medical experts.
Citation: Journal of Medical Engineering and Technology (1998), 22(4): 160-167
URI: https://doi.org/10.3109/03091909809032534
http://repository.iitr.ac.in/handle/123456789/7113
Issue Date: 1998
Publisher: Taylor & Francis Ltd, London
ISSN: 3091902
Author Scopus IDs: 6602605137
25646515800
57204684351
Author Affiliations: Vijaya, G., Department of ECE, REC, Warangal, India
Kumar, V., Department of Electrical Engineering, UOR, Roorkee, India, Department of Electrical Engineering, UOR, Roorkee-247667, UP, India
Verma, H.K., Department of Electrical Engineering, UOR, Roorkee, India
Funding Details: The authors acknowledge the generosity of late Professor Jos L. Willems, project leader, Div. Medical Informatics, University Hospital, Gasthuisberg, Leuven, Belgum for providing the CD-ROM, 'Common standards for quantitative Electrocardiography (CSE) multi-lead library'. The authors express their gratitude to the Dep$rtment of Electrical Engineering, University of Roorkee for providing the necessary facilities to carry out this work. The authors are grateful to Major Rajat Datta, Medical Specialist, Military Hospital, Roorkee for the invaluable expertise and help offered during the software validation. G. Vijaya is also grateful to the Regional Engineering college, Warangal, which has sponsored him for his Doctoral progam and the All India Council for Technical Education (AICTE), New Delhi for providing financial assistance. Last but not least, the authors also acknowledge the anonymous referees for their constructive comments. The authors also thank the medical experts consulted for their invaluable suggestions.
Corresponding Author: Kumar, V.; Department of Electrical Engineering, UOR, Roorkee-247667, UP, India
Appears in Collections:Journal Publications [EE]

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