Respiration Measurement Technology Based on Inertial Sensors：A Review

被引：0
作者：
Fang, Xudong [1 ,2 ,3 ,4 ,5 ]
Deng, Wubin [1 ,2 ,3 ,4 ]
Wu, Zutang [6 ]
Li, Jin [6 ]
Wu, Chen [1 ,2 ,3 ,4 ]
Maeda, Ryutaro [1 ,2 ,3 ,4 ]
Tian, Bian [1 ,2 ,3 ,4 ,5 ]
Zhao, Libo [1 ,2 ,3 ,4 ,5 ]
Lin, Qijing [1 ,2 ,3 ,4 ,5 ]
Zhang, Zhongkai [1 ,2 ,3 ,4 ,5 ]
Han, Xiangguang [1 ,2 ,3 ,4 ,5 ]
Jiang, Zhuangde [1 ,2 ,3 ,4 ,5 ]
机构：
[1] School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an
[2] State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an
[3] International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University, Xi’an
[4] Xi’an Jiaotong University (Yantai), Research Institute for Intelligent Sensing Technology and System, Xi’an Jiaotong University, Xi’an
[5] Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing, Yantai
[6] Northwest Nuclear Technology Institute, Xi’an
来源：
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | 2024年 / 60卷 / 20期
关键词：
accelerometers; imu; inertial sensors; physiological parameter monitoring; respiration measurement; respiratory rate; wearable devices;
D O I：
10.3901/JME.2024.20.001
中图分类号：
学科分类号：
摘要：
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. © 2024 Chinese Mechanical Engineering Society. All rights reserved.
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页码：1 / 23
页数：22
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共 115 条
  • [61] GAIDHANI A, MOON K, OZTURK Y, Et al., Extraction and analysis of respiratory motion using wearable inertial sensor system during trunk motion[J], Sensors, 17, 12, (2017)
  • [62] CESAREO A, GANDOLFI S, PINI I, Et al., A novel，low cost ， wearable contact-based device for breathing frequency monitoring[C], 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2402-2405, (2017)
  • [63] CESAREO A, PREVITALI Y, BIFFI E, Et al., Assessment of breathing parameters using an inertial measurement unit (IMU)-based system[J], Sensors, 19, 1, (2018)
  • [64] CESAREO A, BIFFI E, CUESTA-FRAU D, Et al., A novel acquisition platform for long-term breathing frequency monitoring based on inertial measurement units[J], Medical & Biological Engineering & Computing, 58, 4, pp. 785-804, (2020)
  • [65] RODES C E, CHILLRUD S N，, HASKELL W L, Et al., Predicting adult pulmonary ventilation volume and wearing complianceby on-board accelerometry during personal level exposure assessments[J], Atmospheric Environment, 57, pp. 126-137, (2012)
  • [66] TELFER B A, WILLIAMSON J R, WEED L, Et al., Estimating sedentary breathing rate from chest-worn accelerometry from free-living data[C], 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 4636-4639, (2020)
  • [67] RAHMAN M M, AHMED T, AHMED M Y, Et al., Towards motion-aware passive resting respiratory rate monitoring using earbuds[C], 2021 IEEE 17th International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp. 1-4, (2021)
  • [68] DAN G, ZHAO J, CHEN Z, Et al., A Novel signal acquisition system for wearable respiratory monitoring[J], IEEE Access, 6, pp. 34365-34371, (2018)
  • [69] WANG S, LIU M, PANG B, Et al., A new physiological signal acquisition patch designed with advanced respiration monitoring algorithm based on 3-axis accelerator and gyroscope[C], 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 441-444, (2018)
  • [70] YOON J W, NOH Y S, KWON Y S, Et al., Improvement of dynamic respiration monitoring through sensor fusion of accelerometer and gyro-sensor[J], Journal of Electrical Engineering and Technology, 9, 1, pp. 334-343, (2014)
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