This paper presents a coordinated semi-adaptive approach to closed-loop control of cardiorespiratory state in critically ill patients through the infusion of sedative and opioid drugs. The proposed approach is built upon an upper level multiple drug coordination loop and a lower level semi-adaptive control loop. The coordination loop recursively adjusts the target set points based on the dose-response relationship of a patient estimated by the semi-adaptive control loop, so as to ensure that the target set points become achievable. The semi-adaptive control loop drives the patient state to the target set points while estimating the patient’s dose-response relationship. Hence, the proposed control approach can adjust target set points erroneously specified by caregivers while respond effectively to the need of individual patients. To realize the proposed control approach, we developed (1) a two-input two-output dose-response model of interacting sedative and opioid drugs; (2) a semi-adaptive control algorithm to drive patient state to target set points while selectively estimating high-sensitivity parameters in the dose-response model; and (3) a multiple drug coordination algorithm that reconciles caregiver preference and individual patient’s drug needs. The proposed control approach was evaluated in an example cardiorespiratory control scenario in which cardiac output and respiratory rate are regulated via the infusion of propofol and remifentanil in an in-silico simulation setting. The results show that the coordinated semi-adaptive control could (1) track achievable target set point with robust transient and steady-state error performance and (2) adjust the unachievable target set points to achievable ones.
- Dynamic Systems and Control Division
Coordinated and Semi-Adaptive Cardiorespiratory Control via Sedative and Opioid Drugs
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Jin, X, Kim, C, Shipley, ST, Dumont, GA, & Hahn, J. "Coordinated and Semi-Adaptive Cardiorespiratory Control via Sedative and Opioid Drugs." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems. Tysons, Virginia, USA. October 11–13, 2017. V001T37A004. ASME. https://doi.org/10.1115/DSCC2017-5181
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