Ideal of Fuzzy Inference System and Manifold Deterioration Using Genetic Algorithm and Particle Swarm Optimization

？ Manifold Deterioration Using Genetic Ideal of Fuzzy Inference System and Manifold Deterioration Using Genetic Algorithm and Particle Swarm Optimization is presented. Hypoglycaemia or low blood glucose often occurs with patients that take insulin therapy for diabetes. Hypoglycaemia is serious and causes unconsciousness, seizures or even death. The proposed system uses ECG signal for the detection of hypoglycemia. To find the presence of the hypoglycaemic episodes the system uses heart rate (HR), corrected QT interval, change of HR and change of corrected QT interval of the ECG signal. The system is developed using multiple regression with fuzzy inference system (FIS). Genetic algorithm and particle swarm optimization is used to optimize the parameters of FIS and multiple regressions. Fuzzy Inference System is used to estimate the hypo level based on the physiological parameters. The physiological parameters are heart rate and corrected QT interval. Multiple regressions are used to fine tune the performance of the hypoglycemic detection based on the estimated hypo level and the change of the HR and corrected QT interval. Thus estimate the presence of hypoglycemia using the FIS and multiple regressions with genetic algorithm and also with particle swarm optimation and finally comparing the performance of both techniques