On-line estimation of propofol pharmacodynamic parameters

Sartori, Valentina; Schumacher, Peter; Bouillon, Thomas; Luginbuehl, Martin; Morari, Manfred

doi:10.1109/iembs.2005.1616345

Cited by 31 publications

(28 citation statements)

References 6 publications

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“…In reference [65], a standard PK/PD model was proposed in which the authors assumed that only the PD parameters were responsible for the inter-patient variability, and an extended PK model was used and the model was linearized with the PD parameters identified via a Kalman filter.…”

Section: Challengesmentioning

confidence: 99%

Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia

Navarro-Guerrero

Tang

2018

Algorithms

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Abstract:The design of a fractional-order closed-loop model reference adaptive control (FOCMRAC) for anesthesia based on a fractional-order model (FOM) is proposed in the paper. This proposed model gets around many difficulties, namely, unknown parameters, lack of state measurement, inter and intra-patient variability, and variable time-delay, encountered in controller designs based on the PK/PD model commonly used for control of anesthesia, and allows to design a simple adaptive controller based on the Lyapunov analysis. Simulations illustrate the effectiveness and robustness of the proposed control.

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Section: Challengesmentioning

confidence: 99%

Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia

Navarro-Guerrero

Tang

2018

Algorithms

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“…These values are adjusted to reflect the patient's own parameters over time, based on the observed response of the individual patient under varying circumstances [42]. The Kalman filter will apply a recursive method to calculate numbers for a given doseresponse relationship for the specific patient, for example to individualize the constant for plasma-effect site equilibration [43,44]. Fuzzy logic control is based on fuzzy set theory as proposed by Zadeh [45] in the sixties.…”

Section: Control Methodsmentioning

confidence: 99%

Automated Drug Delivery in Anesthesia

Neckebroek

Smet²,

Struys

2012

Curr Anesthesiol Rep

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Automated drug administration by closed-loop systems has been proposed to optimize drug administration during anesthesia and sedation. Closed-loop systems are able to make decision on their own and try to reach and maintain a preset target. This review describes the milestones and recent development in automated drug delivery systems applicable during sedation, anesthesia and postoperative pain relief.

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“…Since infusion pumps are able to deliver drugs at various pre-programmed con- centrations over time, we require a dynamical model of the drug as it is absorbed (and possibly metabolized) by the various cells in the patient's body and removed from the blood stream. We therefore use pharmacokinetic models to capture such effects over time [26,39,41]. A pharmacokinetic model uses multiple compartments, representing the various systems such as the vascular system, organs such as the liver, kidneys and the skin.…”

Section: Patient Modelmentioning

confidence: 99%

“…Our approach models the infusion pump by composing a simple hybrid automaton, incorporating a model of the pump, along the lines of the generic infusion pump model proposed by Arney et al [2] and the patient using a pharmacokinetic model that describes the concentration of the drug in various parts of the patient's body as the infusion proceeds over time [26,39,41]. Mechanical failures are modeled using failure mode variables and transitions.…”

Section: Introductionmentioning

confidence: 99%

Model-Based Dependability Analysis of Programmable Drug Infusion Pumps

Sankaranarayanan

Homaei

Lewis

2011

Lecture Notes in Computer Science

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Abstract. Infusion pumps are commonly used in home/hospital care to inject drugs into a patient at programmable rates over time. However, in practice, a combination of faults including software errors, mechanical failures and human error can lead to catastrophic situations, causing death or serious harm to the patient. Dependability analysis techniques such as failure mode effect analysis (FMEA) can be used to predict the worst case outcomes of such faults and facilitate the development of remedies against them. In this paper, we present the use of model-checking to automate the dependability analysis of programmable, real-time medical devices. Our approach uses timed and hybrid automata to model the real-time operation of the medical device and its interactions with the care giver and the patient. Common failure modes arising from device failures and human error are modeled in our framework. Specifically, we use "mistake models" derived from human factor studies to model the effects of mistakes committed by the operator. We present a case-study involving an infusion pump used to manage pain through the infusion of analgesic drugs. The dynamics of analgesic drugs are modeled by empirically validated pharmacokinetic models. Using model checking, our technique can systematically explore numerous combinations of failures and characterize the worse case effects of these failures.

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On-line estimation of propofol pharmacodynamic parameters

Cited by 31 publications

References 6 publications

Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia

Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia

Automated Drug Delivery in Anesthesia

Model-Based Dependability Analysis of Programmable Drug Infusion Pumps

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