Arnhold Lohse

Acute respiratory distress syndrome (ARDS) is a disease that has a high reported mortality rate. The treatment for ARDS typically involves mechanical ventilation that is tailored to each patient's needs. A crucial aspect of this treatment is maintaining adequate oxygen saturation of haemoglobin by setting the fraction of inspired oxygen. This paper proposes a design method of robust proportional-integral-derivative (PID) controllers using a gas exchange model during ARDS. Several PID controllers were synthesized for different sub-operational ranges defined by measurable quantities of the mechanical ventilator and the patient using a mixed sensitivity H∞ approach. In simulations, the controller demonstrated high robustness to external changes and changes in the patient's condition, with saturation always above 88%. Although further validation of the controller is required, the results indicate that the presented robust control method has the potential to be clinically relevant.

Mechanical ventilation is essential in intensive care treatment but leads to diaphragmatic atrophy, which in turn contributes to prolonged weaning and increased mortality. One approach to prevent diaphragmatic atrophy while achieving pulmonary ventilation is electrical stimulation of the phrenic nerve. To automize phrenic nerve stimulation resulting in lung protective tidal volumes with lowest possible currents, mathematical models are required. Nerve stimulation models are often complex, so many parameters have to be identified prior to implementation. This paper presents a novel, simplified approach to model phrenic nerve excitation to obtain an individualized patient model using a few data points. The latter is based on the idea that nerve fibers are excited when the electric field exceeds a threshold. The effect of the geometry parameter on the model output was analyzed, and the model was validated with measurement data from a pig trial (RMSE in between 0.44 × 10⁻² and 1.64 × 10⁻² for parameterized models). The modeled phrenic nerve excitation behaved similarly to the measured tidal volumes, and thus could be used to develop automated phrenic nerve stimulation systems for lung protective ventilation.