High-frequency percussive ventilation (HFPV) is a non-conventional mechanical ventilatory strategy which has proven useful in the treatment of a number of pathological conditions.
HFPV usually involves the usage of endotracheal tubes (EET) connecting the ventilator circuit to the airway of the patient.
The pressure of the air flow insufflated by HFPV must be controlled very accurately in order to avoid barotrauma and volutrauma.
Since the actual tracheal pressure cannot be measured, a model for estimating such a pressure based on the EET properties and on the air flow properties that can actually be measured in clinical practice is necessary.
In this work we propose a novel methodology, based on Genetic Programming, for synthesizing such a model.
We experimentally evaluated our models against the state-of-the-art baseline models, crafted by human experts, and found that our models for estimating tracheal pressure are significantly more accurate.
