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机械通气是临床上用于改善患者呼吸的重要辅助手段,所以机械通气参数设定的正确与否直接影响着患者体内的气体交换过程。本文尝试建立一种基于人体肺部气体交换数学模型的机械通气模糊逻辑决策系统。人体肺部气体交换数学模型可以根据患者的生理参数模拟出患者的肺部气体交换情况,便于临床医生更好地了解和掌握患者的病情。决策系统应用模糊控制的方法提出适合患者的机械通气设定参数,为临床医生进行机械通气的设置提供参考。实验选取10名在ICU接受机械通气治疗的患者,系统根据每一位患者的生理参数建立了相应的气体交换数学模型,并提供了适合患者的机械通气设定参数,与患者当前接受的机械通气设定参数进行对比。结果表明系统提出的机械通气设定参数在满足患者气体交换要求的前提下尽可能地降低了吸入氧浓度的值,在满足分钟通气量的前提下尽可能地降低患者呼吸功,改善了患者的气体交换情况。
Mechanical ventilation is clinically used to improve the patient’s breathing is an important adjunct to the mechanical ventilation parameters set correctly or not directly affects the body’s gas exchange process. This paper attempts to establish a mechanical ventilation fuzzy logic decision-making system based on the mathematical model of human lung gas exchange. The mathematical model of human lung gas exchange can simulate the patient’s lung gas exchange according to the physiological parameters of the patient so that the clinician can better understand and master the patient’s condition. The decision-making system applies the fuzzy control method to put forward the mechanical ventilation setting parameters suitable for the patients, which provides reference for the clinicians to set up the mechanical ventilation. The experiment selected 10 patients undergoing mechanical ventilation in the ICU. The system established a mathematical model of gas exchange based on the physiological parameters of each patient and provided the parameters suitable for the patient’s mechanical ventilation to communicate with the patient’s currently accepted mechanical ventilation Set the parameters for comparison. The results showed that the system proposed parameters of mechanical ventilation to meet the gas exchange requirements of patients under the premise of as much as possible to reduce the value of inhaled oxygen concentration in meeting the minute ventilation under the premise of minimizing the patient’s work of breathing to improve the patient’s Gas exchange situation.