{"title":"基于PSO的麻醉深度单神经元PID控制器的FPGA实现","authors":"Layla H. Abood, Ekhlas H. Karam, Abbas H. Issa","doi":"10.1109/SCEE.2018.8684186","DOIUrl":null,"url":null,"abstract":"Anesthesia is considered as one of the most important part of any surgical operation due to this it must be good monitored and controlled, i.e. the rate of infusion must be given an inappropriate dose to save the patient status in an adequate level of anesthesia. The model translates the relation between the drug used and patient response is pharmacokinetic pharmacodynamic (PK/PD). Bispectral index (BIS) is the most standard for maintaining the Anesthesia level. In this paper an optimal PID controller with neural network consists of one neuron is presented to evaluate the drug infusion rate, the system input will be the propofol drug rate, and the level of hypnosis will be the system output since it is measured during surgery from the monitor of the BIS device. optimal controller will calculate the infusion rate by using particle swarm optimization (PSO) method for tuning all the variables needed to find the optimal rate and considered it as a control signal. Then all the result is obtained by Matlab software and the hardware implantation is done using the Integrated Synthesis Environment from Xilinx ISE version 14.6 and downloaded on Spartan 3 Kit (XC3SD3400ACS484-4 by). The output results obtained from the controller in measuring the value of the infusion rate and tracking the BIS value for different patients show its efficiency and robustness in measuring the Depth of Anesthesia (DOA) correctly.","PeriodicalId":357053,"journal":{"name":"2018 Third Scientific Conference of Electrical Engineering (SCEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"FPGA Implementation of Single Neuron PID Controller for Depth of Anesthesia Based on PSO\",\"authors\":\"Layla H. Abood, Ekhlas H. Karam, Abbas H. Issa\",\"doi\":\"10.1109/SCEE.2018.8684186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Anesthesia is considered as one of the most important part of any surgical operation due to this it must be good monitored and controlled, i.e. the rate of infusion must be given an inappropriate dose to save the patient status in an adequate level of anesthesia. The model translates the relation between the drug used and patient response is pharmacokinetic pharmacodynamic (PK/PD). Bispectral index (BIS) is the most standard for maintaining the Anesthesia level. In this paper an optimal PID controller with neural network consists of one neuron is presented to evaluate the drug infusion rate, the system input will be the propofol drug rate, and the level of hypnosis will be the system output since it is measured during surgery from the monitor of the BIS device. optimal controller will calculate the infusion rate by using particle swarm optimization (PSO) method for tuning all the variables needed to find the optimal rate and considered it as a control signal. Then all the result is obtained by Matlab software and the hardware implantation is done using the Integrated Synthesis Environment from Xilinx ISE version 14.6 and downloaded on Spartan 3 Kit (XC3SD3400ACS484-4 by). The output results obtained from the controller in measuring the value of the infusion rate and tracking the BIS value for different patients show its efficiency and robustness in measuring the Depth of Anesthesia (DOA) correctly.\",\"PeriodicalId\":357053,\"journal\":{\"name\":\"2018 Third Scientific Conference of Electrical Engineering (SCEE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Third Scientific Conference of Electrical Engineering (SCEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCEE.2018.8684186\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Third Scientific Conference of Electrical Engineering (SCEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCEE.2018.8684186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
摘要
麻醉被认为是任何外科手术中最重要的部分之一,因此麻醉必须得到良好的监测和控制,即必须给予适当剂量的输注速度,以在适当的麻醉水平下挽救患者的状态。该模型将所用药物与患者反应之间的关系转化为药代动力学(PK/PD)。双谱指数(BIS)是维持麻醉水平的最标准指标。本文提出了一个由一个神经元组成的神经网络的最优PID控制器来评估药物输注速率,系统输入为异丙酚药物速率,催眠水平作为系统输出,因为它是在手术过程中从BIS设备的监视器中测量到的。最优控制器将利用粒子群优化(PSO)方法对寻找最优速率所需的所有变量进行整定,并将其作为控制信号来计算注入速率。然后通过Matlab软件获得所有结果,并使用Xilinx ISE 14.6版集成合成环境进行硬件植入,并下载到Spartan 3 Kit (xc3sd3400acs484 - 4by)上。控制器测量不同患者的输液速率值和跟踪BIS值的输出结果表明,控制器在正确测量麻醉深度(Depth of Anesthesia, DOA)方面具有高效性和鲁棒性。
FPGA Implementation of Single Neuron PID Controller for Depth of Anesthesia Based on PSO
Anesthesia is considered as one of the most important part of any surgical operation due to this it must be good monitored and controlled, i.e. the rate of infusion must be given an inappropriate dose to save the patient status in an adequate level of anesthesia. The model translates the relation between the drug used and patient response is pharmacokinetic pharmacodynamic (PK/PD). Bispectral index (BIS) is the most standard for maintaining the Anesthesia level. In this paper an optimal PID controller with neural network consists of one neuron is presented to evaluate the drug infusion rate, the system input will be the propofol drug rate, and the level of hypnosis will be the system output since it is measured during surgery from the monitor of the BIS device. optimal controller will calculate the infusion rate by using particle swarm optimization (PSO) method for tuning all the variables needed to find the optimal rate and considered it as a control signal. Then all the result is obtained by Matlab software and the hardware implantation is done using the Integrated Synthesis Environment from Xilinx ISE version 14.6 and downloaded on Spartan 3 Kit (XC3SD3400ACS484-4 by). The output results obtained from the controller in measuring the value of the infusion rate and tracking the BIS value for different patients show its efficiency and robustness in measuring the Depth of Anesthesia (DOA) correctly.