Ventricular Fabrication Prediction Approach Based on Cloud-Mobile Healthcare Platform

Abstract

Sudden Cardiac Death (SCD) is an important risk factor for primary Ventricular Fibrillation (VF). This paper presents a prediction algorithm of VF based on Cloud-Mobile Healthcare platform. This algorithm applies heart rate variability (HRV) features and neural fuzzy network. The neural fuzzy network's input features are obtained by linear and nonlinear features of HRV. The experimental results show that the combination of features can predict VF by the accuracy of 65% for the five minutes intervals, before VF occurrence. It has been implemented in Cloud-Mobile Healthcare Platform. This Cloud-Mobile Healthcare Platform meets heart patient's requirements of early detection of outside the hospital.