There are significant variations in healthy nasal airflow patterns, so it is difficult to identify a universal template for normal nasal airflow. In the case of diseased nasal cavities, the flow present even more random characteristics than the healthy ones. For this reason, a consensus has not been reached yet for what constitutes normal nasal airflow patterns. In addition, there is no general agreement regarding the identification of different diseases after examining only the nasal airflow. In this work, we introduce two dimensionless mathematical estimators for helping in the medical diagnosis of human nasal cavities. In general, these estimators take low values for healthy cavities and high values for nasal cavities with a disease. Basically, these estimators need only global information as nasal geometrical parameters or fluid magnitudes determinated by computational fluid dynamics (CFD) simulations.
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