An Adaptive Multi-critic Neuro-fuzzy Control Framework for Intravenous Anesthesia Administration

作     者：Khodaei, Mohammad Javad Balaghi I., M. Hadi Mehrvarz, Amin Jalili, Nader 

作者机构：PhD Student Piezoactive Systems Laboratory Department of Mechanical Industrial Engineering Northeastern University BostonMA02115 United States  Eindhoven Netherlands Professor and Author of Correspondence Department Head of Mechanical Engineering The University of Alabama TuscaloosaAL United States Affiliate Professor Department of Mechanical Industrial Engineering Northeastern University BostonMA United States 

出 版 物：《IFAC-PapersOnLine》 

年 卷 期：2019年第51卷第34期

页      面：202-207页

核心收录：

主　　题：Controllers Anesthesiology Closed loop control systems Controlled drug delivery Drug infusion Fuzzy control Fuzzy inference Fuzzy neural networks Surgery Closed loops Fuzzy controllers Inter intra patient variability Intravenous anesthesias Surgical disturbances 

摘      要：Development of closed-loop control strategies for drug infusion and delivery is one of the most recent efforts of control engineers and clinicians. This can be used especially in anesthesia during different surgeries to stabilize the patient in the desired awareness condition. In this paper, an adaptive neuro-fuzzy controller is proposed to overcome the current challenges in closed-loop control of anesthesia such as inter and intra patient variability, complex and nonlinear dynamics, measurement noises and surgical disturbances as well as the presence of undershoot and overshoot in the induction phase. The results show an acceptable performance of the proposed controller in solving these problems by providing a learning scheme. © 2019