A fast Critical Arrhythmic ECG waveform identification method using cross-correlation and multiple template matching

Critical Arrhythmic ECG such as Ventricular Tachycardia (VT) and Ventricular Fibrillation (VF) are both distinguishable by its waveform characteristics. A VF waveform is often described as disorganized and has an irregular rhythm while a VT waveform exhibits abnormal signatures and presents a regular rhythm pattern. This paper presents a fast cross-correlation algorithm using multiple waveform templates for automatic detection of life threatening arrhythmias such as VT and VF from the Normal Sinus Rhythm (NSR) waveforms. A sliding-window template cross-correlation technique is applied to an ECG signal to generate an array of correlation coefficients. Then a correlation coefficient curve is used to detect high coefficient values for a type of template that will quantify the similarity between an examined ECG signal and a template. The method presented in this paper is able to detect all three different types of ECG signals from a total 21 testing signal set with a satisfied correct rate.