基于RFID技术的医疗设备信息技术研究

Research on Information Technology of Medical Equipment Based on RFID Technology

目的针对医疗设备数据处理速度慢及诊断正确率低等现象,提出一种基于无线射频识别(Radio Frequency Identification,RFID)技术的医疗设备信息技术研究方法。方法利用RFID定位技术,将蚁群算法融入人工智能算法的神经网络模型中,实现对医疗仪器的准确定位。同时采用基于模糊理论的医疗设备故障诊断模型,将提取的故障特征信号进行信息融合,判断医疗设备有无故障,并经过模糊理论的决策推理后,确定仪器故障的原因。最后采用连续蚁群算法优化人工智能算法中的神经网络模型权值,用RFID系统采集的信号分类强度数据测试算法,训练反射信号的模型,提升该算法的全局搜索效率。结果实验结果表明,改进后的人工智能算法在医疗设备信息的识别跟踪和定位方面,准确率在90%以上,最高可达97%。结论本研究方法能够有效提高医疗设备信息的识别和定位准确度,为提高医疗诊断正确率提供有力支持。

Objective Aiming at the problems of slow data processing speed and low diagnostic accuracy of medical equipment,to propose a research method of medical equipment information technology based on radio frequency identification(RFID)technology.Methods RFID positioning technology was used,the ant colony algorithm was integrated into the neural network model of artificial intelligence algorithm,and the accurate positioning of medical instruments was realized.At the same time,the medical equipment fault diagnosis model based on fuzzy theory was used to fuse the extracted fault characteristic signals to judge whether the medical equipment had faults,and the reason of the instrument fault was determined after the decision reasoning of fuzzy theory.Finally,the continuous ant colony algorithm was used to optimize the weight of the neural network model in the artificial intelligence algorithm,and the signal classification strength data collected by the RFID system was used to test the algorithm and train the reflected signal model,aiming at improving the global search efficiency of the algorithm.Results The experimental results showed that the accuracy of the improved artificial intelligence algorithm in the identification,tracking and positioning of medical equipment information was more than 90%,up to 97%.Conclusion This research method can effectively improve the identification and positioning accuracy of medical equipment information,and provide strong support for improving the accuracy of medical diagnosis.