智能控制器可生成有助于降低血压的地氟醚浓度值。

IF 1.3 Q4 ENGINEERING, BIOMEDICAL
Medical Devices-Evidence and Research Pub Date : 2024-10-26 eCollection Date: 2024-01-01 DOI:10.2147/MDER.S483837
Pawel Ratajczyk, Bartosz Dominikowski, Agnieszka Czylkowska, Bartlomiej Rogalewicz, Cezary Kulak, Tomasz Gaszynski
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引用次数: 0

摘要

导言:本文旨在确定地氟醚的适当浓度,以有效抵消手术压力导致的血压升高。在医疗实践中,通常通过使用额外剂量的阿片类药物来限制血压升高。额外使用药物或增加已使用药物的剂量可能会对您的健康产生不利影响。在麻醉过程中,医生必须注意药物的使用情况并记住它们,尤其是最近使用过的药物,这些药物会影响医生的注意力。为此,作者决定为选择地氟醚浓度提供支持,从而不必频繁使用阿片类药物。作者使用了一个基于人工智能问题的系统来完成这项任务。学习后的系统通过模仿麻醉师的工作为其提供支持:所提出的地氟醚浓度选择方法以模糊控制器为基础。该系统包括一个学习机制,可将操作误差降至最低。该系统的主要优点是能够在不了解过程数学描述的情况下建立一个允许选择麻醉参数的函数。要完成这项任务,需要有一名专家提供信息,以构建逻辑上的 "如果-那么 "句子(空间中的点)。模糊控制器将考虑空间中的点适当连接起来,生成一个超曲面。算法测试仅通过计算机进行,没有患者参与:结果:通过计算机模拟验证了拟议算法的运行。文章作者分析了获得的结果与专家提供的表格是否一致。计算机模拟得出的地氟醚浓度值与表格中给出的值相近。最小的驾驶误差不会影响患者的临床反应。这种误差来自模糊系统中使用的函数及其设置。所提算法的性能测试结果以时间过程呈现,其形状为阶跃函数。该作品提出了一个函数,可以输入人体反应达到所需的 Etdes 水平所需的时间:在这项研究中,创建了一个控制器来支持地氟醚浓度的选择,从而降低血压(手术压力导致的血压)。计算机模拟得出的结果为优化麻醉提供了有价值的见解。该系统还可用作重要的教学模拟程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Generating Controller a Desflurane Concentration Value Which Helps to Decrease Blood Pressure.

Introduction: The aim of the article is to determine the appropriate concentration of desflurane to effectively counteract the increase in blood pressure resulting from surgical stress. In medical practice, this increase is often limited by using additional doses of opioid drugs. Additional medications or higher doses of those already used may adversely affect your health. During anesthesia, physician must note the use of drugs and remember them, especially those that he has recently administered, which affect his concentration. For this purpose, the authors decided to propose support for the selection of desflurane concentration so that frequent use of opioid drugs is not necessary. The authors used a system based on AI issues to accomplish this task. The learned system supports the anesthesiologist's work by imitating him.

Patients and methods: The proposed method for selecting the desflurane concentration is based on a fuzzy controller. This system includes a learning mechanism that allows for minimizing the operating error. The main advantage of this system is the ability to build a function allowing the selection of anesthesia parameters without knowledge of the mathematical description of the process. To accomplish this task, you need an expert who will provide information in the construction of logical if-then sentences (points in space). The fuzzy controller connects the points in the consideration space appropriately, generating a hypersurface. The algorithm test was performed only by computer without the participation of patients.

Results: The operation of the proposed algorithm was verified by computer simulation. The authors of the article analyzed the compliance of the obtained results with the table provided by the expert. The desflurane concentration values obtained by computer simulation are similar to those given in the table Minimal driver error does not affect the patient's clinical response. This error results from the functions used in the fuzzy system and its settings. The results of the performance test of the proposed algorithm are presented in a time course, and it has the shape of a step function. The work proposes a function that allows you to enter the time needed for the body's reaction to reach the desired Etdes level.

Conclusion: In this study, a controller was created to support the selection of the concentration of desflurane allowing for a reduction in blood pressure (resulting from surgical stress). The results obtained by computer simulation provide valuable insights for optimizing anesthesia. This system can also be used as an important simulation program for teaching purposes.

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来源期刊
Medical Devices-Evidence and Research
Medical Devices-Evidence and Research ENGINEERING, BIOMEDICAL-
CiteScore
2.80
自引率
0.00%
发文量
41
审稿时长
16 weeks
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