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基于Petri网的医疗监测系统的规范与验证

Specification and Verification of Medical Monitoring System Using Petri-nets.

作者信息

Majma Negar, Babamir Seyed Morteza

机构信息

Department of Computer, University of Kashan, Kashan, Iran ; Department of Computer, Naghshejahan Higher Education Institute, Isfahan, Iran.

Department of Computer, University of Kashan, Kashan, Iran.

出版信息

J Med Signals Sens. 2014 Jul;4(3):181-93.

Abstract

To monitor the patient behavior, data are collected from patient's body by a medical monitoring device so as to calculate the output using embedded software. Incorrect calculations may endanger the patient's life if the software fails to meet the patient's requirements. Accordingly, the veracity of the software behavior is a matter of concern in the medicine; moreover, the data collected from the patient's body are fuzzy. Some methods have already dealt with monitoring the medical monitoring devices; however, model based monitoring fuzzy computations of such devices have been addressed less. The present paper aims to present synthesizing a fuzzy Petri-net (FPN) model to verify behavior of a sample medical monitoring device called continuous infusion insulin (INS) because Petri-net (PN) is one of the formal and visual methods to verify the software's behavior. The device is worn by the diabetic patients and then the software calculates the INS dose and makes a decision for injection. The input and output of the infusion INS software are not crisp in the real world; therefore, we present them in fuzzy variables. Afterwards, we use FPN instead of clear PN to model the fuzzy variables. The paper follows three steps to synthesize an FPN to deal with verification of the infusion INS device: (1) Definition of fuzzy variables, (2) definition of fuzzy rules and (3) design of the FPN model to verify the software behavior.

摘要

为了监测患者行为,医学监测设备从患者身体收集数据,以便使用嵌入式软件计算输出结果。如果软件不符合患者需求,计算错误可能危及患者生命。因此,软件行为的准确性是医学领域关注的问题;此外,从患者身体收集的数据是模糊的。已经有一些方法用于监测医学监测设备;然而,基于模型的此类设备模糊计算监测方法较少被涉及。本文旨在提出合成一个模糊Petri网(FPN)模型,以验证一种名为持续输注胰岛素(INS)的样本医学监测设备的行为,因为Petri网(PN)是验证软件行为的形式化和可视化方法之一。该设备由糖尿病患者佩戴,然后软件计算胰岛素剂量并做出注射决策。在现实世界中,输注胰岛素软件的输入和输出并非清晰明确;因此,我们将它们表示为模糊变量。之后,我们使用FPN而非清晰的PN对模糊变量进行建模。本文通过三个步骤合成一个FPN来处理输注胰岛素设备的验证:(1)定义模糊变量,(2)定义模糊规则,(3)设计FPN模型以验证软件行为。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ae/4187353/ea16d9603ba3/JMSS-4-181-g001.jpg

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