Abstract: The present application discloses a complexity-based method for synthetically detecting ventricular fibrillation, which centers on complexity calculations while incorporating a plurality of feature values and thus differentiates more effectively among various types of ECG signals. The method further modifies the complexity algorithm, making it more adapted to reflecting characteristics of the VF-related signals, thereby enabling high sensitivity and specificity of detection. Further, the related calculation load is reduced according to the algorithm. As such, the method can fully satisfy the clinical needs and is aimed for solving the problems of low sensitivity, low specificity and weak anti-interference ability present in current medical equipment for detecting ventricular fibrillation, such as monitors, implanted cardioversion defibrillator (ICD), automatic external defibrillator (AED) and so on. Systems for performing the method are also disclosed.