On an Automatic Intravenous Anesthesia Control System

近年来，静脉麻醉药异丙酚相继问世，与其他麻醉药相比，异丙酚具有副作用小、药效好等优点。在本研究中，我们研究了麻醉深度指数和异丙酚静脉麻醉控制方法，旨在开发一种自动静脉麻醉控制系统，使患者的麻醉深度保持在适当的水平，并以最少的药物输注。具体地说，我们研究了1)合适的麻醉深度指标，2)麻醉深度对异丙酚输注反应的数学模型，3)采用模型预测控制的麻醉深度控制系统。结果表明：在心血管动力学指标、中位功率频率(MF)、频谱边缘频率(SEF 95)和BIS中，双谱指数(BIS)是反映麻醉深度的最佳指标。根据手术中麻醉药物输注和BIS数据，建立了描述麻醉药物输注量、血药浓度、效应点浓度与BIS之间关系的数学模型，该模型由四阶传递函数与死区时间和非线性函数组成。此外，由于死区时间和描述效应点浓度与BIS之间关系的非线性函数存在很大的个体差异，我们开发了一种从麻醉引入时的麻醉药物输注和BIS数据中识别它们的方法。为了评估系统的准确性和可靠性，我们在与实际操作类似的扰动下进行了仿真。结果表明，我们的系统具有足够的性能。

Recently, an intravenous anesthetic drug, propofol, which has less side effects and better characteristics than the other anesthetic drugs is developed. In this research, we have studied an index of anesthetic depth and an intravenous anesthesia control method using propofol in order to develop an automatic intravenous anesthesia control system for keeping patients' anesthetic depth at an appropriate level with minimal infusion of drug. To be concrete, we have studied 1) an appropriate index of anesthetic deptlt, 2) mathematical model of the response of the anesthetic depth to propofol infusion, and 3) a control system of the anesthetic depth using model predictive control. The obtained results are as follows.Bispectral index (BIS) is the best index of anesthetic depth among the index of cardiovascular dynamics, median power frequency (MF), spectral edge frequency (SEF 95) and BIS.From the data of anesthetic drug infusion and BIS during surgical operations, we made a mathematical model which describes the relation among the anesthetic drug infusion, the drug concentration in blood, effect-site concentration and BIS.The model consists of four-order transfer function with dead time and nonlinear function. Furthermore, since the dead time and the nonlinear function which describes the relation between effect-site concentration and BIS have much individual difference, we have developed a method of identifying them from the data of anesthetic drug infusion and BIS during anesthesia introduction.We have developed an intravenous anesthesia control system using model predictive control. To evaluate the accuracy and reliability of our system, we made simulations under similar disturbances as in the actual operations. The results indicated that our system has enough performance.