Lin Hui-Hing, Beck Carolyn L, Bloom Marc J
Department of Mechanical and Industrial Engineering, University of Illinois, Urbana, IL 61801, USA.
IEEE Trans Biomed Eng. 2004 Nov;51(11):1876-87. doi: 10.1109/TBME.2004.831541.
The standard modeling paradigm used to describe the relationship between input anesthetic agents and output patient endpoint variables are single-input single-output pharmacokinetic-pharmacodynamic (PK-PD) compartment models. In this paper, we propose the use of multivariable piecewise-linear models to describe the relations between inputs that include anesthesia, surgical stimuli and disturbances to a variety of patient output variables. Subspace identification methods are applied to clinical data to construct the models. A comparison of predicted and measured responses is completed, which includes predictions from PK-PD models, and piecewise-linear time-invariant models.
用于描述输入麻醉剂与输出患者终点变量之间关系的标准建模范式是单输入单输出药代动力学-药效学（PK-PD）房室模型。在本文中，我们建议使用多变量分段线性模型来描述包括麻醉、手术刺激和干扰在内的输入与各种患者输出变量之间的关系。将子空间识别方法应用于临床数据以构建模型。完成了预测响应与测量响应的比较，其中包括来自PK-PD模型和分段线性时不变模型的预测。
