This article introduces a new strategy to detect a ventricular premature beat (VPB). The strategy utilized a swarm fuzzy inference system (SFIS) and features of the R wave of electrocardiogram. SFIS was a FIS optimized using particle swarm optimization (PSO). The PSO was used to find the optimal parameters of the FIS. The fuzzification part of the FIS used a Gaussian function. The inputs of the FIS were the width and the gradient of the R wave. Using clinical data, the proposed strategy performed well for VPB detection with sensitivity, specificity and accuracy of 99.05%, 99.64% and 99.59%, respectively. © 2013 IEEE.
Nuryani N., Yahya I., Lestari A.
Proceeding – IEEE CYBERNETICSCOM 2013: IEEE International Conference on Computational Intelligence and Cybernetics, 10.1109/CyberneticsCom.2013.6865790