A study of IOS data using two mead-related models of respiratory impedance.

This paper introduces two new respiratory system models, the Mead-Cw model and the Mead-Cl 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 Cw and Cl). 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-Cl model and the Mead-Cw model also yielded unreasonably large values for Cw and Cl, 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.