Lozano S, Möller K, Brendle A, Gottlieb D, Schumann S, Stahl C A, Guttmann J
Department of Biomedical Engineering, Furtwangen University, Villingen-Schwenningen Campus, Germany.
Technol Health Care. 2008;16(1):1-11.
A closed-loop system (AUTOPILOT-BT) for the control of mechanical ventilation was designed to: 1) autonomously achieve goals specified by the clinician, 2) optimize the ventilator settings with respect to the underlying disease and 3) automatically adapt to the individual properties and specific disease status of the patient. The current realization focuses on arterial oxygen saturation (SpO(2)), end-tidal CO(2) pressure (P(et)CO(2)), and positive end-expiratory pressure (PEEP) maximizing respiratory system compliance (C(rs)). The "AUTOPILOT-BT" incorporates two different knowledge sources: a fuzzy logic control reflecting expert knowledge and a mathematical model based system that provides individualized patient specific information. A first evaluation test with respect to desired end-tidal-CO(2)-level was accomplished using an experimental setup to simulate three different metabolic CO(2) production rates by means of a physical lung simulator. The outcome of ventilator settings made by the "AUTOPILOT-BT" system was compared to those produced by clinicians. The model based control system proved to be superior to the clinicians as well as to a pure fuzzy logic based control with respect to precision and required settling time into the optimal ventilation state.
设计了一种用于控制机械通气的闭环系统（AUTOPILOT-BT），其目的是：1）自主实现临床医生指定的目标；2）根据潜在疾病优化呼吸机设置；3）自动适应患者的个体特性和特定疾病状态。当前的实现方式侧重于动脉血氧饱和度（SpO₂）、呼气末二氧化碳分压（PₑₜCO₂）以及使呼吸系统顺应性（Cᵣₛ）最大化的呼气末正压（PEEP）。“AUTOPILOT-BT”纳入了两种不同的知识源：反映专家知识的模糊逻辑控制和基于数学模型的系统，该系统提供患者个体化的特定信息。使用实验装置通过物理肺模拟器模拟三种不同的代谢性二氧化碳产生速率，完成了针对期望呼气末二氧化碳水平的首次评估测试。将“AUTOPILOT-BT”系统做出的呼吸机设置结果与临床医生做出的结果进行了比较。在精度和进入最佳通气状态所需的稳定时间方面，基于模型的控制系统被证明优于临床医生以及纯模糊逻辑控制。
