Wavelet and energy based approach for PVC detection

This paper describes a wavelet and energy based technique for the detection of ventricular premature arrhythmic beats in Electrocardiogram (ECG) that are of great importance in evaluating and predicting life threatening ventricular arrhythmias. Premature Ventricular Contraction (PVC) can be seen in ECG as abnormal wave shape of the QRS complex. A new scheme is proposed for the detection of premature ventricular beats, which is a vital function in rhythm monitoring of cardiac patients. The method for classifying the abnormal complexes from the normal ones is based on the concepts of RR-interval of detected R peaks and energy analysis of ECG signal. ECG R-peaks have been detected by wavelet method in which ECG signal has been decomposed to the required level by selected wavelet and the selected detail coefficient d4 by energy, frequency and correlation analysis undergoes thresholding and decision logic to detect R-peaks. An RR-interval window is placed between the two successive R-peaks when the RR-interval exceeds beyond a predefined threshold. Furthermore, window based energy analysis of ECG signal is performed by eliminating the low frequency samples and a higher energy window beyond a predefined threshold is analyzed. An intersection of these two windows gives rise actual number and positions of PVCs in the ECG signal.