Study on Analgesia Control in Balanced Anesthesia

在这项研究中，我们开发了一个在日间手术中使用模型预测控制器的自动催眠和止痛控制系统。首先，我们提出了一个结合脉搏频率和脑电频谱分析得到的熵差的指标作为日间手术的镇痛指标，并证实该指标可以用于调整瑞芬太尼的输注速度。然后，考虑药物和死亡时间的相互作用，建立了异丙酚和瑞芬太尼的催眠和镇痛反应模型。此外，我们还开发了麻醉诱导过程中个体参数的识别功能。仿真结果表明，所开发的系统具有良好的性能。

In this study, we have developed an automatic hypnosis and analgesia control system during day-case surgery using a model predictive controller. First, we proposed an index combining pulse rate and the Entropy Difference obtained by spectral analysis of electroencephalogram as an analgesia index available during day-case surgery, and confirmed that the index can be used for adjusting infusion rate of remifentanil. Then, we constructed a model of hypnosis and analgesia responses to propofol and remifentanil considering interaction of the drugs and dead times. Furthermore, we developed an identification function of individual parameters during anesthesia induction. The simulation results show that the developed system has a good performance.