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作 者:房珂宇 张鑫 王钧钧 秦晓丽 陈平[1] FANG Ke-yu;ZHANG Xin;WANG Jun-jun;QIN Xiao-li;CHEN Ping(Systems Engineering Institute,Academy of MIlitary Sciences of the PLA,Tianjin 300161,China)
出 处:《医疗卫生装备》2024年第9期14-20,共7页Chinese Medical Equipment Journal
基 金:军队科研项目(145AHQ140005000X)。
摘 要:目的:设计一种基于光学字符识别(optical character recognition,OCR)模型的医疗救治装备数据采集平台,以实现应急灾害救援条件下医疗数据的自动化采集。方法:该平台以医疗物联网“感知—网络—平台”架构为基础构建。首先,选取Raspberry Pi 4B作为边缘节点,使用视频采集卡、摄像头、平板计算机等搭建硬件环境。其次,基于卷积循环神经网络(convolutional recurrent neural network,CRNN)优化OCR模型,通过软硬件协同方式实现医疗终端视频流处理与数据提取。最后,采用FineBI工具实现交互界面设计与数据库链接。结果:经实验验证,该平台的硬件环境可靠、稳定,优化后的OCR模型文本识别准确率提升,且采用该平台能够实现对医疗设备数据的快速、自动化采集。结论:采用该平台能够为医护人员提供全面、准确的医疗救治装备数据支撑,有利于提升医疗救治效率。Objective To design a data collection platform for medical treatment equipment based on an optical character recognition(OCR)model to facilitate auto medical data acquisition during emergency disaster relief.Methods A data collection platform for medical treatment equipment was constructed with the"perception—network—platfrom"architecture of medical Internet of Things.Firstly,Raspberry Pi 4B was adopted as the edge node,and the hardware environment was established with the video capture card,camera and tablet computer.Secondly,the OCR model was optimized based on convolutional recurrent neural network(CRNN),and video stream processing and data extraction at the the medical terminal were realized through hardware and software collaboration.Finally,FineBI tool was used to implement interactive interface design and database link.Results The platform developed was proved by experiments to have its hardware environment gifted with high reliability and stability and the optimized OCR model with enhanced text recognition accuracy,which contributed to rapid and automatic data acquisition for medical equipment.Conclusion The platform developed provides comprehensive and accurate medical treatment equipment data support for medical personnel,which is conducive to enhancing the efficiency of medical treatment.
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