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Rule Extraction By Fuzzy Modeling Algorithm For Fuzzy Logic Control Of Cisatracurium As A Neuromuscular Block

机译:模糊建模算法的神经肌肉阻滞曲沙库铵的模糊逻辑控制规则提取

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This paper provides two rule bases to control administration of cisatracurium, a non-depolarizing neuromuscular blocking agent. One rule base is extracted from the objective approach of fuzzy modeling algorithm (FMA), and the other is from the subjective approach of experts' clinical experience. First, we established the data-acquisition system to record the manual neuromuscular block control during surgery. After collecting 15 patients data control by cisatracurium, we extracted six rules from these data via FMA. Another rule base also had six rules from experts with clinical anesthesia experience. Each rule-base was combined with three rules regarding the safety of the fuzzy controller. To compare their performance through simulations, we used the patient model established by our previous study which is a combination model consisting of a three-compartment mathematical model based on pharmacokinetics, and the Hill equation based on pharmacodynamics. In order to test the differences between these two rule-bases, the simulation used four disturbances: the different set points, the control interval strategy, the tolerance of noise effect, and the tolerance of delay time effect. The simulation shows that the FMA could successfully extract the fuzzy rules from the clinical data, and its control error is smaller than expert rules for different set point tests. However, the control error is increased and becomes worse when the set points are raised, which means that these two rule-bases are not appropriate to control the higher set points (i.e. T1% of 40 or higher). The t-test also shows that these two rule-bases performance of different set points have significant differences (p<0.05). Moreover, the results for control interval tests show that strategy has a significant influence, especially in reducing the standard deviation of control error. However, in simulations, these two rule-bases are not affected by noise disturbance, and the delay time affects only the overshoot for these two rule-bases.
机译:本文提供了两个规则库来控制顺沙曲库铵(一种非去极化的神经肌肉阻滞剂)的给药。一种规则库是从模糊建模算法(FMA)的客观方法中提取的,另一种是从专家的临床经验的主观方法中提取的。首先,我们建立了数据采集系统来记录手术过程中的手动神经肌肉阻滞控制。在通过西沙曲库收集了15位患者的数据后,我们通过FMA从这些数据中提取了6条规则。另一个规则库也有来自具有临床麻醉经验的专家的六个规则。每个规则库都与关于模糊控制器安全性的三个规则结合在一起。为了通过仿真比较其性能,我们使用了先前研究建立的患者模型,该模型是一个组合模型,由基于药代动力学的三室数学模型和基于药效学的Hill方程组成。为了测试这两个规则库之间的差异,模拟使用了四个干扰:不同的设定点,控制间隔策略,噪声影响的容限和延迟时间影响的容限。仿真表明,FMA可以成功地从临床数据中提取模糊规则,其控制误差小于针对不同设定点测试的专家规则。但是,当设定点升高时,控制误差会增加并变得更糟,这意味着这两个规则库不适合控制较高的设定点(即40%或更高的T1%)。 t检验还表明,不同设定点的这两个规则库性能具有显着差异(p <0.05)。此外,控制间隔测试的结果表明,该策略具有显着影响,尤其是在减小控制误差的标准偏差方面。但是,在仿真中,这两个规则库不受噪声干扰的影响,并且延迟时间仅影响这两个规则库的过冲。

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