Abstract
Ventricular Fibrillation (VF) and Ventricular Tachycardia (VT) are arrhythmia which seriously endangers the patient's life, as we know that electrical defibrillation is a most effective way that can rescue their lives. There are some similarities among signals of ventricular flutter (VFL), cardiac arrest, VF and VT; so erroneous judgments may occur by shock able (ShR) signal detection algorithm, which made the patients suffer unnecessary electric shocks. For this reason, a novel method which can distinguish VF and VT rapidly and accurately by ShR signal detection is urgently needed. Approximate entropy, which is a nonlinear dynamic parameters used for measuring sequence complexity and statistical quantification, has been attempted to distinguish various arrhythmias, and preferable results have achieved.
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