Semiadaptive Infusion Control of Medications With Excitatory Dose-Dependent Effects

This brief presents a closed-loop control approach to infusion of medications that exhibit excitatory dose-dependent effects. A unique challenge associated with closed-loop control of such medications is that the upper limit of the medication-induced excitatory response is unknown, presenting a seve...

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Bibliographic Details
Published in:IEEE transactions on control systems technology 2019-07, Vol.27 (4), p.1735-1743
Main Authors: Zhu, Junxi, Jin, Xin, Bighamian, Ramin, Kim, Chang-Sei, Shipley, Steven T., Hahn, Jin-Oh
Format: Article
Language:English
Subjects:
Adaptation models
Analytical models
Computer simulation
Control design
Controllers
Data models
Dose-response model
Heart rate
Mathematical model
Mathematical models
medication infusion
Norepinephrine
Parameter estimation
Parameter sensitivity
Parameterization
physiological closed-loop control
semiadaptive (SA) control
Sensitivity
System identification
vasopressor
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Summary:This brief presents a closed-loop control approach to infusion of medications that exhibit excitatory dose-dependent effects. A unique challenge associated with closed-loop control of such medications is that the upper limit of the medication-induced excitatory response is unknown, presenting a severe challenge in estimating the parameters in the traditional dose-response model. To address this challenge, we proposed a new dose-response model and semiadaptive (SA) control approach applicable to the closed-loop infusion control of excitatory medications. The new dose-response model eliminates the need for a priori knowledge of the upper limit of the medication-induced response via a novel parameterization to capture local dose-response relationship from the baseline to a target set point and a nonlinear function to convert the depressive response to an excitatory response. The SA control approach makes it possible to apply the well-established MRAC technique to the new dose-response model via selective adaptation of high-sensitivity parameters. We examined the efficacy of the proposed approach using an example of heart rate response to a vasoactive medication norepinephrine. System identification analysis using experimental data and in-silico controller testing suggested that the new dose-response model could faithfully reproduce the experimental data, and that the SA controller could effectively regulate the response in a wide range of simulated subjects.
ISSN:1063-6536
1558-0865
DOI:10.1109/TCST.2018.2815551