RT Conference Proceedings
T1 Model and neural control of the depth of anesthesia during surgery
A1 Fernández-de-Cañete-Rodríguez, Francisco Javier
A1 Medina, Mayte
A1 Fernández de Cañete, Rafael
A1 Alcain, Nuria
A1 Ramos-Diaz, Juan Carlos
K1 Anestesia
AB At present, the experimentation of anesthetic drugs onpatients requires a regulation protocol, and the response of each patientto several doses of entry drug must be well known. Therefore, thedevelopment of pharmacological dose control systems is a promisingfield of research in anesthesiology.In this paper it has been developed a non-linear compartmentalpharmacokinetic-pharmacodynamical model which describes theanesthesia depth effect on a sufficiently reliable way over a set ofpatients with the depth effect quantified by the Bi-Spectral Index.Afterwards, an Artificial Neural Network (ANN) predictive controllerhas been designed based on the depth of anesthesia model so as to keepthe patient on the optimum condition while he undergoes surgicaltreatment.For the purpose of quantifying the efficiency of the neural predictivecontroller, a classical proportional-integral-derivative controller hasalso been developed to compare both strategies. Results show thesuperior performance of predictive neural controller during Bi-Spectral Index reference tracking.
PB WASET
YR 2018
FD 2018
LK https://hdl.handle.net/10630/15350
UL https://hdl.handle.net/10630/15350
LA eng
NO WASET  Conference Barcelona Spain Feb 27-28, 2018, 20 (2) Part XXIII
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026