Abstract: An efficient algorithm to estimate a respiratory system nonlinear model of sedated patients under assisted ventilation is presented. The considered model comprises an airways resistance and a volume-dependant compliance and, for each respiratory cycle, the proposed algorithm provides online the model parameters guaranteeing a minimum accuracy, above a user-defined threshold. Relying on standard nonlinear identification techniques, it exhibits computational burden reduction features, which contribute to its suitability for its online application.
Diego A. Riva, Carolina A. Evangelista, Paul F. Puleston, "Efficient Algorithm for Pulmonary Nonlinear Model Online Estimation of Patients Under Assisted Ventilation," WSEAS Transactions on Biology and Biomedicine, vol. 20, pp. 257-266, 2023, DOI:10.37394/23208.2023.20.27
Diego A. Riva, Carolina A. Evangelista, Paul F. Puleston. Efficient Algorithm for Pulmonary Nonlinear Model Online Estimation of Patients Under Assisted Ventilation.
WSEAS Transactions on Biology and Biomedicine. 2023;20:257-266. 10.37394/23208.2023.20.27