Modelling oxygen delivery to spontaneously breathing individuals: improving oxygenation using a feedback controller.

This study employed a simulation approach to model oxygen delivery in spontaneously breathing patients with chronic obstructive pulmonary disease (COPD). The Morozoff Model, originally designed for mechanically ventilated patients with a fixed fraction of inspired oxygen (FIO2), was adapted to incorporate the relationship between oxygen flow delivered through nasal cannula and FIO2, along with COPD-specific pathophysiological parameters. The effectiveness of constant and variable oxygen flow delivery was evaluated using a closed-loop control system with a Proportional-Integral-Derivative (PID) controller. The adapted Morozoff Model successfully replicated SpO2 variations observed in COPD patients, capturing desaturation patterns during rapid eye movement sleep and daily activities. Simulations showed that continuous oxygen flow was inadequate for maintaining SpO2 within the target range. Evaluating the closed-loop control system, a proportional (P) controller was found to be sufficient, with integral (I) and derivative (D) terms having negligible impact on performance for a baseline case. The proportional controller improved SpO2 regulation, increasing time within the target range (88%-92%) to 80%, compared to a maximum of 55% achieved with a constant oxygen flow system. However, as airway resistance increased compared to the baseline case, the controller's performance declined, highlighting the need for re-tuning P and potentially incorporating I and D terms to improve adaptability under varying pathophysiological parameters. In addition, more advanced control strategies, such as model-based controllers, may enhance adaptability to dynamic patient conditions. These findings support the development of adaptive oxygen delivery strategies for spontaneously breathing COPD patients.