A Study of IOS Data Using Two Mead-related Models of Respiratory Impedance

This paper introduces two new respiratory system models, the Mead-C_w model and the Mead-C_I model, which are 6-component models that are intermediate in complexity between the well-known 7-component Mead model and the recently proposed 5-component augmented RIC model (derived from the Mead model by eliminating both C_w and C_t). Their modeling errors were compared to the RIC, extended RIC, augmented RIC and Mead models, for component values estimated from IOS data. The two new models yielded lower errors than all the other models, except for the Mead model. However, the Mead-C_I model and the Mead-C_w model also yielded unreasonably large values for C_w and C_I, respectively, which are known disadvantages of the Mead model. Hence the augmented RIC model appears to be the most useful at present for IOS-based computer- aided detection and diagnosis of respiratory disorders.