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• W4289534145 abstract "A variety of automatic control systems are increasingly being deployed to assist clinicians to monitor patient functioning and enhance healthcare delivery during surgical procedures. This article deals with the mathematical design framework of closed-loop infusion schemes for propofol delivery in general anesthesia. The main emphasis of this research series is to come up with a better-performing control system which could handle the clinical concerns of automation-based anesthesia without compromise of safety. Also, the research is geared at studying the performance of these plausible control-based automatic drug infusion patterns in a computer environment prior to actual clinical implementation. The study advances the design of effective model-based predictive control (MPC) strategies familiar to engineers in the process industries, as well as a preliminary design of a proportional–integral–derivative (PID) controller. The consideration of the traditional PID controller is followed by two linear MPC strategies and a nonlinear one. These varieties of closed-loop infusion strategies were designed in order to make well-informed comparison and assessment of the promising method(s) of control for the sought clinical application. The successive linearization technique is being applied in novelty to anesthesia in this work. The results indicate that the MPC controllers show great promise for adoption for automated drug delivery in anesthesia delivering better performance. This sets the pace for future investigations which may assess, via pseudo-clinical in silico studies, the deployment of the controllers." @default.
• W4289534145 created "2022-08-03" @default.
• W4289534145 creator A5033462873 @default.
• W4289534145 date "2022-04-28" @default.
• W4289534145 modified "2023-10-02" @default.
• W4289534145 title "Exploratory mathematical frameworks and design of control systems for the automation of propofol anesthesia" @default.
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• W4289534145 doi "https://doi.org/10.1007/s40435-022-00953-1" @default.
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