Nonlinear identification algorithm for online and offline study of pulmonary mechanical ventilation
Diego A Riva,
Carolina A Evangelista,
Paul F Puleston
et al.
Abstract:This work presents an algorithm for determining the parameters of a nonlinear dynamic model of the respiratory system in patients undergoing assisted ventilation. Using the pressure and flow signals measured at the mouth, the model’s quadratic pressure–volume (P–V) characteristic is fit to these data in each respiratory cycle by appropriate estimates of the model parameters. Parameter changes during ventilation can thus also be detected. The algorithm is first refined and assessed using data derived from simul… Show more
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