title: [Particle swarm optimization fuzzy modeling and closed-loop anaesthesia control based on cerebral state index].
abstract: Due to individual differences of the depth of anaesthesia (DOA) controlled objects, the drawbacks of monitoring index, the traditional PID controller of anesthesia depth could not meet the demands of nonlinear control. However, the adjustments of the rules of DOA fuzzy control often rely on personal experience and, therefore, it could not achieve the satisfactory control effects. The present research established a fuzzy closed-loop control system which takes the cerebral state index (CSI) value as a feedback controlled variable, and it also adopts the particle swarm optimization (PSO) to optimize the fuzzy control rule and membership functions between the change of CSI and propofol infusion rate. The system sets the CSI targets at 40 and 30 through the system simulation, and it also adds some Gaussian noise to imitate clinical disturbance. Experimental results indicated that this system could reach the set CSI point accurately, rapidly and stably, with no obvious perturbation in the presence of noise. The fuzzy controller based on CSI which has been optimized by PSO has better stability and robustness in the DOA closed loop control system.
authors.forename: Jingtian
authors.initials: J
authors.lastname: Tang
authors.forename: Yang
authors.initials: Y
authors.lastname: Cao
authors.forename: Jiaying
authors.initials: J
authors.lastname: Xiao
authors.forename: Qulian
authors.initials: Q
authors.lastname: Guo
mesh_terms: D000758:Anesthesia / Q000379:methods*; D000776:Anesthesiology / Q000379:methods; D018686:Anesthetics, Intravenous / Q000008:administration & dosage; D005246:Feedback; D017143:Fuzzy Logic; D015742:Propofol / Q000008:administration & dosage*
chemical_list: D018686:Anesthetics, Intravenous; D015742:Propofol