基于Sugeno模型的监护仪使用状态评价研究

Research on evaluation of monitor usage state based on Sugeno model

目的:基于Sugeno模型实现对监护仪使用状态快速准确的评价。方法:采用自适应神经网络模糊系统(adaptive network-based fuzzy inference system,ANFIS),通过MATLAB平台中的Sugeno模型构建监护仪使用状态评价模型,以监护仪已使用时间、平均环境相对湿度、平均环境温度、电源电压、已发生故障次数和电磁干扰程度等因素为输入参数,以监护仪使用状态分类等级为输出结果,对监护仪使用状态进行评价。将基于Sugeno模型模糊推理得到的评价结果与实际结果进行对比,以验证模型的可靠性和准确性。结果:基于Sugeno模型推理得到的监护仪使用状态与实际使用状态基本一致。结论:基于Sugeno模型的监护仪使用状态评价方法可以对监护仪当前的使用状态进行快速准确评价,有助于医护人员及时掌握监护仪的使用状态,提升了监护仪在医疗过程中的可靠性。

Objective To achieve a rapid and accurate evaluation of the usage state of the monitor based on the Sugeno model.Methods The adaptive network-based fuzzy inference system(ANFIS)was used to construct a monitor usage status evaluation model by using the Sugeno model in the MATLAB platform.The evaluation of the usage status of the monitor was implemented using the factors such as the time the monitor had been in use,the average ambient relative humidity,the average ambient temperature,the power supply voltage,the number of faults that had occurred and the degree of electromagnetic interference as the input parameters and the grade of the monitor's usage status as the output result.The evaluation results based on the fuzzy inference of the Sugeno model were compared with the actual results to verify the reliability and accuracy of the model.Results The results obtained based on the Sugeno model was generally consistent with the actual usage status of the monitor.Conclusion The Sugeno model-based monitor usage evaluation method provides a quick and accurate evaluation of the current usage status of the monitor,which helps medical staffs to keep track of the monitor's usage status and improves the reliability of the monitor in medical operations.