Wu Y J, Wu Z L, Wang L, et al. Respiratory rate monitoring system based on inorganic halide perovskite humidity sensor[J]. Opto-Electron Eng, 2021, 48(3): 200100. doi: 10.12086/oee.2021.200100
Citation: Wu Y J, Wu Z L, Wang L, et al. Respiratory rate monitoring system based on inorganic halide perovskite humidity sensor[J]. Opto-Electron Eng, 2021, 48(3): 200100. doi: 10.12086/oee.2021.200100

Respiratory rate monitoring system based on inorganic halide perovskite humidity sensor

    Fund Project: National Key R & D Plan for Major Instruments (2016YFF0102802), Chongqing Key Instrument Project (cstc2017zdcy-zdzxX0009), Funded by Special Fund for Performance Incentive Guidance of Scientific Research Institutions in Chongqing (cstc2019jxjl130029), Chongqing Natural Science Foundation (cstc2018jcyjA3233, cstc2019jcyj- msxmX0623), Fundamental Scientific Research Business of Central Universities (2018CDQYGD0008, 2018CDXYGD0017, 2019CDQYGD004), and Chongqing Graduate Research and Innovation Project (CYS19011)
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  • The traditional respiratory rate measurement technologies have several deficiencies, such as subjective appraised results, complicated signal extraction processes, difficult access to equipment, and inconvenience to move due to the wired connection setting. The respiratory airflow can directly reflect the human breath, and the respiratory frequency is usually 10~12 breaths/min (1 ventilation every 5~6 seconds). The humidity difference between exhalation and inhalation can be directly used to measure respiratory rate. In the present work, a wireless respiratory rate monitoring system based on inorganic halide perovskite humidity sensor was developed. The sensor exhibits an ultrasensitive humidity sensing performance, which overcomes the long response/recovery time (> 10 seconds) of the commercial humidity sensors. The system utilized a Zigbee wireless communication to transmit the measurement signal, which separates the signal detection and processing parts, making it easier for the tester to move. The upper computer software was designed and used for data processing to calculate the breathing rate. The system can accurately monitor the respiratory rate in real-time, recognize and alarm the apnea successfully by comparing with a setting threshold value. The test results show that the system can accurately monitor the breathing rate with a maximum error of 1 time per minute. The system possesses great potential for application in respiratory rate monitoring due to its high accuracy, simple operation, portability, and low cost.
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  • [1] Cretikos M A, Bellomo R, Hillman K, et al. Respiratory rate: the neglected vital sign[J]. Med J Aust, 2008, 188(11): 657-659. doi: 10.5694/j.1326-5377.2008.tb01825.x

    CrossRef Google Scholar

    [2] Allen J. Photoplethysmography and its application in clinical physiological measurement[J]. Physiol Meas, 2007, 28(3): R1-R39. doi: 10.1088/0967-3334/28/3/R01

    CrossRef Google Scholar

    [3] Hogan J. Why don't nurses monitor the respiratory rates of patients?[J]. Br J Nurs, 2006, 15(9): 489-492. doi: 10.12968/bjon.2006.15.9.21087

    CrossRef Google Scholar

    [4] 陈星池, 赵海, 毕远国, 等. 手机可见光提取脉搏中呼吸率的估计[J]. 东北大学学报(自然科学版), 2017, 38(7): 932-935.

    Google Scholar

    Chen X C, Zhao H, Bi Y G, et al. Respiratory rate estimation from smartphone-camera-acquired pulse wave signal using visible light[J]. J Northeast Univ (Nat Sci), 2017, 38(7): 932-935.

    Google Scholar

    [5] Pimentel M A F, Johnson A E W, Charlton P H, et al. Toward a robust estimation of respiratory rate from pulse oximeters[J]. IEEE Trans Biomed Eng, 2017, 64(8): 1914-1923. doi: 10.1109/TBME.2016.2613124

    CrossRef Google Scholar

    [6] 陈星池, 赵海, 李晗, 等. 近红外可穿戴设备中脉搏波的呼吸率检测[J]. 光学 精密工程, 2016, 24(6): 1297-1306.

    Google Scholar

    Chen X C, Zhao H, Li H, et al. Detection of respiratory rate using pulse wave on near infrared wearable devices[J]. Opt Precision Eng, 2016, 24(6): 1297-1306.

    Google Scholar

    [7] Charlton P H, Birrenkott D A, Bonnici T, et al. Breathing rate estimation from the electrocardiogram and photoplethysmogram: a review[J]. IEEE Rev Biomed Eng, 2018, 11: 2-20. doi: 10.1109/RBME.2017.2763681

    CrossRef Google Scholar

    [8] 储泰山, 陆美珠, 马志新. 基于床垫式生命监测仪的呼吸率检测[J]. 科技创新与应用, 2014(18): 5-6.

    Google Scholar

    Chu T S, Lu M Z, Ma Z X. Respiratory rate measurement based on mattress life monitor[J]. Technol Innov Appl, 2014(18): 5-6.

    Google Scholar

    [9] Turnbull H, Kasereka M C, Amirav I, et al. Development of a novel device for objective respiratory rate measurement in low-resource settings[J]. BMJ Innovat, 2018, 4(4): 185. doi: 10.1136/bmjinnov-2017-000267

    CrossRef Google Scholar

    [10] Lee P J. Clinical evaluation of a novel respiratory rate monitor[J]. J Clin Monit Comp, 2016, 30(2): 175-183. doi: 10.1007/s10877-015-9697-4

    CrossRef Google Scholar

    [11] 范大勇. 便携式呼吸监测系统设计方案的改进和算法研究[D]. 天津: 天津大学, 2018.

    Google Scholar

    Fan D Y. Improved design and algorithm research of portable respiratory detection system[D]. Tianjin: Tianjin University, 2018.

    Google Scholar

    [12] Zhen Z, Li Z C, Zhao X L, et al. Formation of uniform water microdroplets on wrinkled graphene for ultrafast humidity sensing[J]. Small, 2018, 14(15): 1703848. doi: 10.1002/smll.201703848

    CrossRef Google Scholar

    [13] Smith A D, Elgammal K, Niklaus F, et al. Resistive graphene humidity sensors with rapid and direct electrical readout[J]. Nanoscale, 2015, 7(45): 19099-19109. doi: 10.1039/C5NR06038A

    CrossRef Google Scholar

    [14] Atalay O, Kennon W R, Demirok E. Weft-knitted strain sensor for monitoring respiratory rate and its electro-mechanical modeling[J]. IEEE Sens J, 2015, 15(1): 110-122. doi: 10.1109/JSEN.2014.2339739

    CrossRef Google Scholar

    [15] Zheng Y L, Ding X R, Poon C C Y, et al. Unobtrusive sensing and wearable devices for health informatics[J]. IEEE Trans Biomed Eng, 2014, 61(5): 1538-1554. doi: 10.1109/TBME.2014.2309951

    CrossRef Google Scholar

    [16] Mogera U, Sagade A A, George S J, et al. Ultrafast response humidity sensor using supramolecular nanofibre and its application in monitoring breath humidity and flow[J]. Sci Rep, 2014, 4: 4103.

    Google Scholar

    [17] Borini S, White R, Wei D, et al. Ultrafast graphene oxide humidity sensors[J]. ACS Nano, 2013, 7(12): 11166-11173. doi: 10.1021/nn404889b

    CrossRef Google Scholar

    [18] Adib F, Mao H Z, Kabelac Z E, et al. Smart homes that monitor breathing and heart rate[C]//Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, South Korea, 2015: 837-846.

    Google Scholar

    [19] Iber C, Ancoli-Israel S, Chesson A L, et al. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications[M]. 2nd ed. Westchester, Ill, USA: American Academy of Sleep Medicine, 2012.

    Google Scholar

    [20] Anichini C, Aliprandi A, Gali S M, et al. Ultrafast and highly sensitive chemically functionalized graphene oxide-based humidity sensors: harnessing device performances via the supramolecular approach[J]. ACS Appl Mater Interfaces, 2020, 12(39): 44017-44025. doi: 10.1021/acsami.0c11236

    CrossRef Google Scholar

  • Overview: Respiratory rate, as an important parameter of respiratory function, refers to the number of breaths per minute, and can provide important information related to health status. Continuously, accurately and stably monitoring respiratory rate is great significance for preventing respiratory diseases, cardiovascular diseases. It is simple and accurate to measure breathing rate by measuring the respiratory airflow. However, common airflow detecting methods, such as temperature sensors, piezoelectric sensors, and flow sensors, having weak output signals. There is 30% humidity difference between human exhaled gas with the outside world, humidity sensor can be used to measure the breathing signal. Human breathing frequency from 12 to 20 times per minute. The response and recovery time of the humidity sensors on the market range from ten seconds to tens of seconds, which cannot use to respiratory rate monitoring. When 30% humidity change occurs in the inorganic halide perovskite humidity sensor made in this paper, resistance will change significantly and recover within 3 seconds, which can be used to measure respiratory nasal airflow signals.

    For the convenience of testers, this system uses Zigbee wireless network to transmit signals. The system is divided into four parts: sensor, data acquisition and sending node, receiving node, and host computer software. The data acquiring and sending node collects breathing signal converted by the humidity sensor and sends it to receiving node. Receiving node transmits received data to host computer software. The host computer software processes the received data, and compute respiratory rate through the algorithm. After processing, the relevant information is displayed on the interface for reference by medical staff. From the test data of five testers, it can be seen that under fast, slow, and normal breathing, the maximum error between the system test breathing rate and the tester's actual breathing rate is 1 per minute, and the system can accurately monitor the breathing rate.

    This article designs and develops a respiratory rate monitoring system based on an inorganic halide perovskite humidity sensor, which can accurately measure the breathing process through respiratory airflow. It has a simple structure, a large output signal, a fast response speed, low energy consumption, and is easy to carry. The advantage is that the system's measured breathing results have high accuracy and good circulation stability. The system is expected to be applied in many scenarios such as daily respiratory rate measurement and monitoring of patient respiratory rate in hospitals.

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