Construction of nonlinear dynamical model for artificial respiration and optimal decision of ventilation conditions

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The purpose of this project is to establish modeling methods of respiratory systems and to develop decision methods of optimal ventilation conditions for intelligent monitoring of artificial respiration. In this project, nonlinear dynamical models of respiratory systems are proposed and its parameter estimation methods are given, furthermore developments of applications to artificial respiration are performed for this purpose. Taking features of respiratory systems and usages of the models into consideration, respiratory model with hysteresis elastance and its parameter estimation algorithm, respiratory model considering breath perturbation and measurement noise and its periodical parameter estimation algorithm, respiratory model structure decision method by using GA, fuzzy model of respiratory systems and its parameter estimation algorithm, ant colony optimization method of fuzzy membership functions for fuzzy respiratory model, etc. are developed. These developments construct a framework of modeling respiratory systems and give a bright prospect of intelligent monitoring of artificial respiration.