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Ali Shaban Hassooni
University of Babylon
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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Detection of electrocardiogram QRS complex based on modified adaptive threshold Ehab AbdulRazzaq Hussein; Ali Shaban Hassooni; Hilal Al-Libawy
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (840.34 KB) | DOI: 10.11591/ijece.v9i5.pp3512-3521

Abstract

It is essential for medical diagnoses to analyze Electrocardiogram (ECG signal). The core of this analysis is to detect the QRS complex. A modified approach is suggested in this work for QRS detection of ECG signals using existing database of arrhythmias. The proposed approach starts with   the same steps of previous approaches by filtering the ECG. The filtered signal is then fed to a differentiator to enhance the signal. The modified adaptive threshold method which is suggested in this work, is used to detect QRS complex. This method uses a new approach for adapting threshold level, which is based on statistical analysis of the signal. Forty-eight records from an existing arrhythmia database have been tested using the modified method. The result of the proposed method shows the high performance metrics with sensitivity of 99.62% and a positive predictivity of 99.88% for QRS complex detection.
Co-Authors Ehab AbdulRazzaq Hussein Hilal Al-Libawy