Covariance analysis for practical identifiability of an alveolar recruitment model.

Patient-specific mathematical models of respiratory mechanics can offer substantial insight into patient state and pulmonary dynamics that are not directly measurable. To assure bedside-applicability, the models must be computationally efficient and practically identifiable from the limited available data, while capturing dominant dynamics. This investigation measures the identifiability of a respiratory model for ARDS patients.