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Synthetic Patient Database of Drug Effect in General Anesthesia for Evaluation of Estimation and Control Algorithms

机译：全身麻醉药物综合患者数据库，用于评估估计和控制算法

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This paper describes a database of synthetic patients for the use in estimation and control design in closed-loop anesthesia. The synthetic patients are represented by pharmacokinetic-pharmacodynamic (PKPD) Wiener models for the Depth of Anesthesia estimated from clinical data. The input of the Wiener model is given by the flow rates of propofol and remifentanil while the output is the bispectral index. A positive stable realization of the Wiener model describing the system dynamics is adopted to ensure a biologically feasible behavior of the PKPD system. Both time-varying and time-invariant versions of the models are available. An Extended Kalman filter (EKF) is applied to the clinical data to estimate the patient-dependent parameters of the Wiener model. The time-invariant version of a model is obtained by averaging of the time-varying estimates produced by the EKF. The performance of the Wiener model with estimated parameters is assessed and discussed. To illustrate the utility of the database, a PID controller is evaluated over the synthetic patient cohort.
机译：本文介绍了一个合成患者数据库，用于闭环麻醉的估计和对照设计。通过临床数据估算的麻醉深度的药代动力学-药效学（PKPD）Wiener模型代表了合成患者。维纳模型的输入由丙泊酚和瑞芬太尼的流速给出，而输出是双光谱指数。采用维纳模型描述系统动力学的正稳定实现，以确保PKPD系统的生物学可行行为。模型的时变和时不变版本均可用。将扩展卡尔曼滤波器（EKF）应用于临床数据，以估计Wiener模型与患者相关的参数。通过对EKF产生的时变估计值求平均值，可以得到模型的时不变形式。评估并讨论了带有估计参数的Wiener模型的性能。为了说明数据库的实用性，对综合患者队列评估了PID控制器。

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