|本期目录/Table of Contents|

[1]李文杰,陈长坤,张健,等.基于多参数体征监测的救援人员安全状况实时评估系统研究*[J].中国安全生产科学技术,2025,21(3):21-26.[doi:10.11731/j.issn.1673-193x.2025.03.003]
　LI Wenjie,CHEN Changkun,ZHANG Jian,et al.Research on real-time assessment system for safety status of rescue personnel based on multi-parameter vital sign monitoring[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2025,21(3):21-26.[doi:10.11731/j.issn.1673-193x.2025.03.003]
点击复制

基于多参数体征监测的救援人员安全状况实时评估系统研究*
分享到：

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
21
期数:
2025年3期
页码:
21-26
栏目:
特邀专栏
出版日期:
2025-03-31

文章信息/Info

Title:
Research on real-time assessment system for safety status of rescue personnel based on multi-parameter vital sign monitoring
文章编号:
1673-193X(2025)-03-0021-06
作者:
李文杰; 陈长坤; 张健; 林子达
（中南大学 防灾科学与安全技术研究所，湖南 长沙 410018）
Author(s):
LI Wenjie;  CHEN Changkun;  ZHANG Jian;  LIN Zida
(Institute of Disaster Prevention Science and Safety Technology,Central South University,Changsha Hunan 410018,China)
关键词:
多参数; 救援人员; 安全状况; 实时评估
Keywords:
multi-parameter;  rescue personnel;  safety status;  real-time assessment
分类号:
X924.4
DOI:
10.11731/j.issn.1673-193x.2025.03.003
文献标志码:
A
摘要:
为提高救援人员在救援过程中的安全性，提出1种基于多参数体征监测的救援人员安全状况实时评估系统。在硬件部分，系统采用物联网技术，通过ESP32通信芯片控制器为核心，集成DS18B20体温模块、MAX30102心率血氧模块、S1216F8-BD北斗定位模块和LD2410C雷达模块；软件部分包括数据采集、数据传输、数据管理与分析、交互界面与功能以及警报与响应系统。此外，系统设计基于频域变换的心率血氧运动噪声去除算法，以提高监测数据精准性。通过模拟救援人员在6种不同运动状态下的数据集评估算法性能，控制平均相对误差在4%以内；并基于多参数体征监测的救援人员安全状态预警分析模型，利用人体安全状态医学数据库数据构建智能监测预警算法。研究结果表明：系统可实现对救援人员体温、心率、血氧、运动状态和地理位置的实时监测，并能保证较高的监测数据精准性，同时能够对救援人员的安全状况进行分级评估，并作出预警处理。研究结果可为提高救援人员在复杂救援环境中的安全保障和救援效率提供参考。
Abstract:
To enhance the safety of rescue personnel during the rescue process,a real-time assessment system for the safety status of rescue personnel based on multi-parameter vital sign monitoring was proposed.In the hardware part,the system adopted the Internet of things technology,took the ESP32 communication chip controller as the core,and integrated the DS18B20 body temperature module,MAX30102 heart rate and blood oxygen module,S1216F8-BD Beidou positioning module and LD2410C radar module.The software part included the data acquisition,data transmission,data management and analysis,interactive interface and functionality,as well as alarm and response systems.Additionally,the system designed an exercise noise removal algorithm of heart rate and blood oxygen based on the frequency domain transformation to improve the accuracy of monitoring data.The performance of this algorithm was evaluated by simulating the datasets of rescue personnel in six different exercise states,and the average relative error was controlled within 4%.Based on the early warning analysis model of the safety status of rescue personnel based on multi-parameter vital sign monitoring,an intelligent monitoring and early warning algorithm was constructed by using the medical database data of human safety status.The results show that the system can realize the real-time monitoring of body temperature,heart rate,blood oxygen,exercise state and geographical location of rescue personnel,and can ensure the high accuracy of monitoring data.At the same time,it can conduct the grading assessment on the safety status of rescue personnel and make early warning treatment.The research results can provide reference for improving the safety and rescue efficiency of rescuers in complex rescue environments.

参考文献/References:

［1］郭磊.消防救援人员灾害救援应激反应对救援行动产生的影响和对策研究［J］.水上安全,2024(18):128-132.
［2］李来保.灭火救援中消防员伤亡案例引发的思考［J］.消防科学与技术,2009(4):209-212. LI Laibao.Thought about the casualty of fire fighter in fire fighting and rescue［J］.Fire Science and Technology,2009,28(4):209-212.
［3］左伟.消防员生命体征监测系统的设计与实现［D］.合肥:合肥工业大学,2019.
［4］董炳艳,张自强,徐兰军,等.智能应急救援装备研究现状与发展趋势［J］.机械工程学报,2020,56(11):1-25. DONG Bingyan,ZHANG Ziqiang,XU Lanjun,et al.Research status and development trend of intelligent emergency rescue equipment ［J］.Journal of Mechanical Engineering.2020,56(11):1-25.
［5］陈长坤,谢明峰.基于贝叶斯网络情景分析的含水土质埋压救援现场监测体系研究［J］.中国安全生产科学技术,2023,19(1):109-114. CHEN Changkun,XIE Minfeng.Research on on-site monitoring system of burial rescue in water-bearing soil based on Bayesian network scenario analysis［J］.Journalof Safety Scienceand Technology,2023,19(1):109-114.
［6］彭阳,余芳强,杨祺,等.医院智能应急疏散导航方法与物联网应用研究［J］.中国安全生产科学技术,2022,18(7):213-218. PENG Yang,YU Fangqiang,YANG Qi,et al.Research on intelligent emergency evacuation navigation method and IoT application for hospitals［J］.Journal of Safety Scienceand Technology,2022,18(7):213-218.
［7］YE X,PENG H,LUAO H.Research and practice of IoT technology based on smart campus［J］.Frontiers in Computing and Intelligent Systems,2024,10(1):59-62.
［8］CIRIC R,WOLF DH,POWER JD,et al.Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity［J］.Neuroimage,2017,154:174-187.
［9］DRAGOMIRETSKIY K,ZOSSO D.Variational mode decomposition［J］.IEEE Transactions on Signal Processing,2014,62(3):531-544.
［10］CHEN X L,GUAN J,LIU N B,et al.Maneuvering target detection via radon-rractional fourier transform-based long-time coherent integration［J］.IEEE Transactions on Signal Processing,2014,62(4):939-953.
［11］刘昊东.基于加权支持向量机的建筑工程施工安全预警研究［D］.包头：内蒙古科技大学,2022.
［12］NAMDEO K A,SINGH K D.Challenges in evolutionary algorithm to find optimal parameters of SVM:a review［J］.International Journal of Communication Networks and Information Security,2024,16(4):298-326.
［13］陈家伟.支持向量机在人体健康状态预测中的研究与应用［D］.合肥：中国科学技术大学,2014.
［14］王君贤.基于随机森林与支持向量机的心血管疾病预测研究［D］.天津：天津大学,2018.
［15］石胜源,朱磊,叶琳,等.基于随机森林算法的心血管疾病预测研究［J］.智能计算机与应用,2021,11(4):176-178，181. SHI Shengyuan,ZHU Lei,YE Lin,et al.Disease predict of cardiovascular based on random forest［J］.Intelligent Computer and Applications,2021,11(4):176-178，181.

相似文献/References:

[1]徐明伟,刘冠林,刘昱彤,等.基于JACK的高层救援下肢职业损伤风险特性研究*[J].中国安全生产科学技术,2025,21(2):200.[doi:10.11731/j.issn.1673-193x.2025.02.026]
　XU Mingwei,LIU Guanlin,LIU Yutong,et al.Research on risk characteristics of occupational injury of lower limbs in high-rise rescue based on JACK[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2025,21(3):200.[doi:10.11731/j.issn.1673-193x.2025.02.026]

备注/Memo

备注/Memo:
收稿日期： 2025-01-20
* 基金项目： 国家重点研发计划项目（2021YFC3090403)；中远海运集团资助专项（2024-3-Z002-13)
作者简介： 李文杰，本科生，主要研究方向为智慧消防。
通信作者： 陈长坤，博士，教授，主要研究方向为火灾科学与智慧消防、城市公共安全及应急管理等。
更新日期/Last Update: 2025-03-28