基于超宽带雷达深度学习的人体健康监测系统研究  

Research on Human Health Monitoring System Based on Ultra-Wideband Radar Deep Learning

作　　者：陈晓丹 李浩源 曾伟超 林佳锐 陈新欣 张敏 CHEN Xiaodan;LI Haoyuan;ZENG Weichao;LIN Jiarui;CHEN Xinxin;ZHANG Min(Guangdong Technology College,Zhaoqing 526100,China)

机构地区：[1]广东理工学院,广东肇庆526100

出　　处：《仪表技术》2025年第2期58-62,共5页Instrumentation Technology

基　　金：2023年国家级大学生创新创业项目(202313720003);2023年校级“自动控制与智能检测创新团队”项目(2023TDZK002);2024年校级质量工程项目(KCJJD202401);2024年校级教学资源库项目(JXZYK2024009)。

摘　　要：针对传统人体健康监测存在的准确率低、耗时长问题,设计了一种基于超宽带雷达深度学习的人体健康监测系统。系统核心为STM32F405RGT6芯片,结合PCB双面板、Wi-Fi模块及显示屏模块,实现数据采集与硬件集成。超宽带雷达模块负责捕捉人体生理信号,并通过先进分离算法在检测终端上分离呼吸和心率信号。处理后的数据通过无线网络传输至云端,实现实时远程监控。该系统提升了健康检测的准确性与效率,为医疗领域的疾病预防、临床诊断及长期健康监护提供了重要参考。A human health monitoring system based on ultra-wideband radar deep learning was designed to address the problems of low accuracy and long time consumption in traditional human health monitoring.The system core is STM32F405RGT6 chip,combined with a PCB double-sided board,Wi-Fi module and a display screen module,to achieve data acquisition and hardware integration.The ultra-wideband radar module is responsible for capturing human physiological signals and separating respiratory and heart rate signals on the detection terminal through advanced separa-tion algorithms.The processed data is transmitted to the cloud via wireless network for real-time remote monitoring.This system improves the accuracy and efficiency of health monitoring,providing important references for disease prevention,clinical diagnosis,and long-term health monitoring in the medical field.

关 键 词：超宽带雷达 呼吸频率 心率 非接触性监测 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置] TN957[自动化与计算机技术—控制科学与工程]