• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2024, Vol. 60 ›› Issue (20): 1-23.doi: 10.3901/JME.2024.20.001

• 仪器科学与技术 • 上一篇    下一篇

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基于惯性传感器的呼吸测量技术综述

方续东1,2,3,4,5, 邓武彬1,2,3,4, 吴祖堂6, 李进6, 吴晨1,2,3,4, 前田龙太郎1,2,3,4, 田边1,2,3,4,5, 赵立波1,2,3,4,5, 林启敬1,2,3,4,5, 张仲恺1,2,3,4,5, 韩香广1,2,3,4,5, 蒋庄德1,2,3,4,5   

  1. 1. 西安交通大学机械工程学院 西安 710049;
    2. 西安交通大学机械制造系统工程国家重点实验室 西安 710049;
    3. 西安交通大学微纳制造与测试技术国际合作联合实验室 西安 710049;
    4. 西安交通大学(烟台)智能传感与系统研究院 西安 710049;
    5. 烟台先进材料与绿色制造山东省实验室 烟台 265503;
    6. 西北核技术研究所 西安 710024
  • 收稿日期:2023-09-17 修回日期:2024-04-21 出版日期:2024-10-20 发布日期:2024-11-30
  • 通讯作者: 韩香广,男,1988年出生,博士,助理教授。主要研究方向为MEMS压力传感器。E-mail:xiangguang@xjtu.edu.cn
  • 作者简介:方续东,男,1985年出生,副教授。主要研究方向为智能传感器与微纳测试技术。E-mail:dongfangshuo30@xjtu.edu.cn;赵立波,男,1978年出生,博士,教授,博士研究生导师。主要研究方向为高端MEMS智能传感器与微纳米技术、柔性智能传感与人机交互、量子传感与量子精密测量、能量收集及自供电传感技术。E-mail:libozhao@xjtu.edu.cn
  • 基金资助:
    国家重点研发计划(2020YFB2009100);国家自然科学基金(52175517);之江实验室开放课题(2022MG0AB03)和中央高校基本科研业务费专项资金(xhj032021016-06)资助项目。

Respiration Measurement Technology Based on Inertial Sensors:A Review

FANG Xudong1,2,3,4,5, DENG Wubin1,2,3,4, WU Zutang6, LI Jin6, WU Chen1,2,3,4, MAEDA Ryutaro1,2,3,4, TIAN Bian1,2,3,4,5, ZHAO Libo1,2,3,4,5, LIN Qijing1,2,3,4,5, ZHANG Zhongkai1,2,3,4,5, HAN Xiangguang1,2,3,4,5, JIANG Zhuangde1,2,3,4,5   

  1. 1. School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049;
    2. State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049;
    3. International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi'an Jiaotong University, Xi'an 710049;
    4. Xi'an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and System, Xi'an Jiaotong University, Xi'an 710049;
    5. Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing, Yantai 265503;
    6. Northwest Nuclear Technology Institute, Xi'an 710024
  • Received:2023-09-17 Revised:2024-04-21 Online:2024-10-20 Published:2024-11-30

摘要: 随着对疾病预测和诊断需求的不断增长,面向人民生命健康的科技创新成为迫切需求,监测生理信号的可穿戴装备越来越受到关注。呼吸是反映人体生理状态的重要参数,例如肺炎、睡眠呼吸暂停综合征、肺栓塞等重大疾病往往伴随着人体呼吸参数的变化,监测呼吸参数可以有效地预测和诊断相关疾病,但其可穿戴监测技术尚未取得显著进展。惯性传感器由于低侵入性、重量轻等优点,非常适合开发成监测呼吸信号的可穿戴装备。首先从惯性传感器监测呼吸的发展历程展开,详细论述了惯性传感器监测呼吸的四个发展阶段(呼吸波形的提取、呼吸暂停的识别、睡眠姿态识别以及走跑时的呼吸监测)、惯性传感器监测呼吸的方法以及惯性传感器的数据处理方式。其次,对惯性传感器监测呼吸的不同阶段进行了对比分析,详细地阐述了不同方法的优缺点。再次,对惯性传感器监测呼吸存在的挑战和未来发展方向进行了总结和展望。最后,对基于惯性传感器可穿戴呼吸监测装备的开发提出了一些建议和预测。

关键词: 惯性传感器, 可穿戴装备, 加速度计, IMU, 呼吸测量, 呼吸频率, 生理参数监测

Abstract: With the increasing demand for disease prediction and diagnosis, scientific and technological innovation for people’s life and health has become an urgent need, and wearable equipment for monitoring physiological signals has attracted more and more attention. Respiration is an important parameter that reflects the physiological state of the human body. For example, major diseases such as pneumonia, sleep apnea syndrome, and pulmonary embolism are often accompanied by changes in human respiratory parameters. Monitoring respiratory parameters can effectively predict and diagnose related diseases, but corresponding wearable monitoring technology has yet to make significant progress. Due to the advantages of low invasiveness and light weight, inertial sensors are very suitable to be developed into wearable devices for monitoring breathing signals. Firstly, starting from the development processes of respiration monitoring with inertial sensors, and discusses in detail the four development stages of respiration monitoring with inertial sensors (respiration waveform extraction, apnea recognition, sleep posture recognition, and respiration monitoring when walking and running), the methods of respiration monitoring with inertial sensors, and the approaches of sensor data processing. Secondly, a comparative analysis of different stages of respiration monitoring by inertial sensors is carried out, and the advantages and disadvantages of different methods are described in detail. Thirdly, the challenges and future development directions of inertial sensors for monitoring respiration are summarized and prospected. Finally, some suggestions and predictions are made for the development of wearable respiratory monitoring devices based on inertial sensors.

Key words: inertial sensors, wearable devices, accelerometers, imu, respiration measurement, respiratory rate, physiological parameter monitoring

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