Ventricular Fibrillation Detection using Empirical Mode Decomposition and Approximate Entropy

Efficient detection of ventricular fibrillation is very important for clinical purposes as it is the most serious cardiac rhythm disturbance that can be life threatening. This paper presents a new method for detection of Ventricular fibrillation by discriminating it with Ventricular tachycardia using empirical mode decomposition (EMD) and Approximate Entropy. First Intrinsic mode functions (IMFs) of each ECG signal is used to distinct between them by calculating their approximate Entropy. We have used MIT/BIH database to validate the efficiency of our method. Simulations were carried out in MATLAB environment. The result shows that this method gives good result as accuracy of 91% is achieved for detection of Ventricular fibrillation. Keywords— Accuracy, Approximate Entropy, Empirical mode decomposition, Ventricular fibrillation, Ventricular tachycardia.