Power-Based Optimization of Ventilation Frequency Without Compliance or Resistance Measurements: A Simulation Study
Abstract
Background
Mechanical ventilation remains a life-saving intervention but carries risks such as barotrauma, volutrauma, ergotrauma, and hemodynamic disturbances. Modern ventilators incorporate adaptive strategies to minimize the work of breathing (WOB), often relying on measurements of respiratory resistance and compliance. However, such measurements are prone to error and often unavailable in real time. This study presents a novel adaptive ventilation concept that dynamically identifies the optimal ventilation frequency minimizing WOB per minute without requiring resistance or compliance measurements.
Material and methods
Using a validated hybrid respiratory simulator, we conducted simulation experiments across three representative lung conditions: normal mechanics, decreased compliance, and increased resistance. The system conceptually searched for the ventilation frequency minimizing WOB/min while maintaining constant alveolar ventilation, with the optimization process emulated manually in this proof-of-concept study.
Results
Results confirmed that WOB/min follows a parabolic function of frequency, with optimal frequencies found at 18, 21, and 12 breaths per minute for normal, restrictive, and obstructive patterns, respectively. Importantly, the optimal frequencies aligned with ranges observed in clinical studies of adaptive support ventilation. Furthermore, the system demonstrated natural variability in ventilation rate and tidal volume, which may contribute to alveolar recruitment.
Conclusion
Our findings validate the concept of energy-based optimization of ventilation independent of online lung mechanics assessment. The proposed method is robust, physiologically grounded, and may become suitable for integration into next-generation intelligent ventilators after full automation of the adaptive algorithm. Future work will focus on full automation of the adaptive algorithm and its evaluation in preclinical and clinical studies targeting WOB and mechanical power minimization.
© 2026 Krzysztof Zieliński, Marek Darowski, Tomasz Urbankowski, Maciej Kozarski, Barbara Stankiewicz, Krzysztof Jakub Pałko, Łukasz Kozarski, published by Polish Society of Medical Physics
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