Premature ventricular contraction arrhythmia detection using wavelet coefficients

Premature ventricular contraction (PVC) detection is an important task in critical care medicine. However, making this task automatic is not that simple. In this paper, we are describing a method for PVC arrhythmia detection. This method is based on the use of wavelet detail coefficients to discriminate between normal beats and abnormal beats (PVCs). The proposed method was tested against selected records of the MIT-BIH Arrhythmia Database (MITDB). Results are very satisfactory and show that it is possible to detect PVC arrhythmia using wavelet detail coefficients applied to QRS complexes.

[1]  K. Chan,et al.  Life-threatening ventricular arrhythmia recognition by nonlinear descriptor , 2005, Biomedical engineering online.

[2]  Adel Belouchrani,et al.  QRS detection based on wavelet coefficients , 2012, Comput. Methods Programs Biomed..

[3]  Abdelfatah Charef,et al.  PVC discrimination using the QRS power spectrum and self-organizing maps , 2009, Comput. Methods Programs Biomed..

[4]  Zhao Yan MIT-BIH Arrhythmia Database Signal Generator Based on MSP430 , 2009 .

[5]  W. J. Tompkins,et al.  Estimation of QRS Complex Power Spectra for Design of a QRS Filter , 1984, IEEE Transactions on Biomedical Engineering.

[6]  Mohammad Bagher Shamsollahi,et al.  Robust Detection of Premature Ventricular Contractions Using a Wave-Based Bayesian Framework , 2010, IEEE Transactions on Biomedical Engineering.

[7]  G.B. Moody,et al.  The impact of the MIT-BIH Arrhythmia Database , 2001, IEEE Engineering in Medicine and Biology Magazine.