Nunes Catarina S, Mahfouf Mahdi, Linkens Derek A, Peacock John E
Departamento de Matemática Aplicada, Faculdade de Ciências da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto, Portugal.
Artif Intell Med. 2005 Nov;35(3):195-206. doi: 10.1016/j.artmed.2004.12.004. Epub 2005 Jul 12.
The first part of this research relates to two strands: classification of depth of anaesthesia (DOA) and the modelling of patient's vital signs.
First, a fuzzy relational classifier was developed to classify a set of wavelet-extracted features from the auditory evoked potential (AEP) into different levels of DOA. Second, a hybrid patient model using Takagi-Sugeno Kang fuzzy models was developed. This model relates the heart rate, the systolic arterial pressure and the AEP features with the effect concentrations of the anaesthetic drug propofol and the analgesic drug remifentanil. The surgical stimulus effect was incorporated into the patient model using Mamdani fuzzy models.
The result of this study is a comprehensive patient model which predicts the effects of the above two drugs on DOA while monitoring several vital patient's signs.
This model will form the basis for the development of a multivariable closed-loop control algorithm which administers "optimally" the above two drugs simultaneously in the operating theatre during surgery.
本研究的第一部分涉及两个方面：麻醉深度（DOA）分类和患者生命体征建模。
首先，开发了一种模糊关系分类器，将从听觉诱发电位（AEP）中提取的一组小波特征分类为不同的麻醉深度水平。其次，开发了一种使用高木-菅野模糊模型的混合患者模型。该模型将心率、收缩压动脉压和AEP特征与麻醉药物丙泊酚和镇痛药物瑞芬太尼的效应浓度相关联。使用Mamdani模糊模型将手术刺激效应纳入患者模型。
本研究的结果是一个综合患者模型，该模型在监测患者多个生命体征的同时预测上述两种药物对麻醉深度的影响。
该模型将为多变量闭环控制算法的开发奠定基础，该算法可在手术期间在手术室中“最优地”同时施用上述两种药物。
