Abstract: A system and method based on electrocardiogram (ECG) complexity analysis for real-time detecting shockable ventricular fibrillation (VF) and ventricular tachycardia (VT), and discriminating them from non-shockable tachyarrhythmia (e.g. supraventricular tachycardia (SVT) and atrial fibrillation (AF)) and high-frequency noise. In the disclosed invention, complexity measure CM (0 to 100), quantitatively characterizing the complexity nature of the non-linear dynamics underlying cardiac arrhythmia, is extracted from the sensed patient ECG signal using ECG complexity analysis. From the calculated complexity measure, by three thresholds (low complexity threshold (LCT), mediate complexity threshold (MCT), and high complexity threshold (HCT)), different kinds of tachyarrhythmia (i.e.

Abstract: A cardiac monitor is provided that monitors the condition of the heart of a cardiac patient and generates signals indicating one of several conditions, such as supraventricular tachycardia, ventricular tachycardia and ventricular fibrillation. In order to generate these signals, the ECG from the patient is analyzed to determine a cardiac interval and heart rate, as well as a waveform factor and a waveform factor irregularity. The waveform factor is derived from the average of the ECG amplitudes during a cardiac interval and the peak value of the ECG during the same interval. Preferably, a running average is calculated over several intervals. This waveform factor is then used to detect shockable ventricular arrhythmia. The waveform factor irregularity is indicative of the variability of the waveform factor and is used to differentiate between ventricular tachycardia and ventricular defibrillation.