Nonlinear Modeling and Identification of the Pulmonary Mechanics

In this work, a systematic procedure for the identification of pulmonary system parameters is presented. The proposed algorithm is used with data from a patient with assisted ventilation. The various models utilized are based on physical descriptions of the system with different levels of complexity. After processing the measured signals and applying the identification algorithm, very satisfactory results are achieved, with up to 95;5% fit.