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Philip von Platen
On Physiological Closed-Loop Control for Lung-Protective Mechanical Ventilation
Mechanical ventilation remains the cornerstone of respiratory support and treatment for patients with acute respiratory failure. However, it is a double-edged sword as it can further damage the injured lung. Therefore, its use requires constant and careful adjustment of ventilator parameters, making it workforce-intensive and costly. Physiological closed-loop control of mechanical ventilation presents an opportunity to address some of these challenges.
The respiratory system is the gateway for ventilation and gas exchange, and the small signal behaviour under tidal mechanical ventilation is well-studied. This work dedicates extensive study to the large signal behaviour, which includes the non-linear hysteretic phenomenon that significantly affects the operating points of tidal ventilation. A mathematical Preisach hysteresis model of the respiratory system was developed. Once parameterised, this model could replicate clinically measured pressure-volume curves accurately. Moreover, this model allowed for the simulation of clinical manoeuvres, such as a disconnection from the mechanical ventilator and positive end-expiratory pressure titrations, and lays the foundation for further automation of clinical manoeuvres.
Tight control of the systemic oxygenation is a core requirement for any closed-loop system for mechanical ventilation. Physiological modelling of the disturbed gas exchange was performed to highlight the non-linear, uncertain, and time-varying relationship between the inspired oxygen and the resulting subject’s oxygen saturation, especially in cases of acute lung injury. Closed-loop controllers were designed to focus on reliability, robustness and transparency, and both a rule-based and a robust proportional-integral controller were synthesised. Results from extensive simulations and animal experiments show the controllers to be accurate, reliable and safe despite the significant uncertainties in the process.
A complete physiological closed-loop control system, called SOLVe, is also introduced. It addresses the two main targets of mechanical ventilation strategies, namely gas exchange and lung-protective ventilation, and could adjust all ventilator variables automatically. The system includes four controllers, various continuous physiological measurements and an online estimation of the respiratory mechanics. A heuristic rule-based hierarchy resolves conflicting targets and actions between controllers. Results from two animal trials with pigs demonstrate that the SOLVe system could keep subjects within defined targets while adhering to lung-protective guidelines. At the same time, limited clinical interactions were required during the experiments, suggesting the potential of such a system to reduce clinician workload.
The respiratory system is the gateway for ventilation and gas exchange, and the small signal behaviour under tidal mechanical ventilation is well-studied. This work dedicates extensive study to the large signal behaviour, which includes the non-linear hysteretic phenomenon that significantly affects the operating points of tidal ventilation. A mathematical Preisach hysteresis model of the respiratory system was developed. Once parameterised, this model could replicate clinically measured pressure-volume curves accurately. Moreover, this model allowed for the simulation of clinical manoeuvres, such as a disconnection from the mechanical ventilator and positive end-expiratory pressure titrations, and lays the foundation for further automation of clinical manoeuvres.
Tight control of the systemic oxygenation is a core requirement for any closed-loop system for mechanical ventilation. Physiological modelling of the disturbed gas exchange was performed to highlight the non-linear, uncertain, and time-varying relationship between the inspired oxygen and the resulting subject’s oxygen saturation, especially in cases of acute lung injury. Closed-loop controllers were designed to focus on reliability, robustness and transparency, and both a rule-based and a robust proportional-integral controller were synthesised. Results from extensive simulations and animal experiments show the controllers to be accurate, reliable and safe despite the significant uncertainties in the process.
A complete physiological closed-loop control system, called SOLVe, is also introduced. It addresses the two main targets of mechanical ventilation strategies, namely gas exchange and lung-protective ventilation, and could adjust all ventilator variables automatically. The system includes four controllers, various continuous physiological measurements and an online estimation of the respiratory mechanics. A heuristic rule-based hierarchy resolves conflicting targets and actions between controllers. Results from two animal trials with pigs demonstrate that the SOLVe system could keep subjects within defined targets while adhering to lung-protective guidelines. At the same time, limited clinical interactions were required during the experiments, suggesting the potential of such a system to reduce clinician workload.
Schlagwörter: Mechanical Ventilation; Closed-Loop Control; Robust Control; Physiological Modelling; Hysteresis Modelling
Aachener Beiträge zur Medizintechnik
Herausgegeben von Univ.-Prof. Dr.-Ing. Dr. med. Steffen Leonhardt, Univ.-Prof. Dr.-Ing. Klaus Radermacher und Univ.-Prof. Dr. med. Dipl.-Ing. Thomas Schmitz-Rode, Aachen
Band 78
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