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Estimating Respiratory Mechanical Parameters in Parallel Compartment Models

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2 Author(s)
John G. Eyles ; Department of Medicine, Division of Pulmonary Diseases, University of North Carolina ; Russell L. Pimmel

Four iterative parameter estimation algorithms were used to obtain estimates in three parallel compartment models of the respiratory system. The stability of the parameter estimates and the agreement between the forced random noise impedance data and the model's response were evaluated for each algorithm-model combination. The combination of a two-stage simplex algorithm with a five element model provided the most stable parameter estimates and the second best fit to the data.

Published in:

IEEE Transactions on Biomedical Engineering  (Volume:BME-28 ,  Issue: 4 )