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Methods Inf Med 2022; 61(05/06): 155-166
DOI: 10.1055/s-0042-1757185
Original Article

An Intelligent Medical Isolation Observation Management System Based on the Internet of Things

Wensheng Sun
1   Wireless Communication Teaching and Research Office, School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China
,
Chunmei Wang
1   Wireless Communication Teaching and Research Office, School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China
,
Jimin Sun
2   Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
,
Ziping Miao
2   Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
,
Feng Ling
2   Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
,
Guangsong Wu
3   V.KEL Communications Equipment (Shenzhen) Co. Ltd., Shenzhen, China
› Author Affiliations Funding This work was supported by the Commonwealth Project of the Science and Technology Department of Zhejiang Province (LGF21F010003 and LGF21H260003). None of the funders had any role in the study design, information collection, data analysis and interpretation, or the writing of the article and the decision to submit it for publication. The researchers confirm their independence from the funders and sponsors.
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Abstract

Background Since COVID-19 (coronavirus disease 2019) was discovered in December 2019, it has spread worldwide. Early isolation and medical observation management of cases and their close contacts are the key to controlling the spread of the epidemic. However, traditional medical observation requires medical staff to measure body temperature and other vital signs face to face and record them manually. There is a general shortage of human and personal protective equipment and a high risk of occupational exposure, which seriously threaten the safety of medical staff.

Methods We designed an intelligent crowd isolation medical observation management system framework based on the Internet of Things using wireless telemetry and big data cloud platform remote management technology. Through a smart wearable device with built-in sensors, vital sign data and geographical locations of medical observation subjects are collected and automatically uploaded to the big data monitoring platform on demand. According to the comprehensive analysis of the set threshold parameters, abnormal subjects are screened out, and activity tracking and health status monitoring for medical observation and management objectives are performed through monitoring and early warning management and post-event data traceability. In the trial of this system, the subjects wore the wristwatches designed in this study and real-time monitoring was conducted throughout the whole process. Additionally, for comparison, the traditional method was also used for these people. Medical staff came to measure their temperature twice a day. The subjects were 1,128 returned overseas Chinese from Europe.

Results Compared with the traditional vital sign detection method, the system designed in this study has the advantages of a fast response, low error, stability, and good endurance. It can monitor the temperature, pulse, blood pressure, and heart rate of the monitored subject in real time. The system designed in this study and the traditional vital sign detection method were both used to monitor 1,128 close contacts with COVID-19. There were six cases of abnormal body temperature that were missed by traditional manual temperature measurement in the morning and evening, and these six cases (0.53%) were sent to the hospital for further diagnosis. The abnormal body temperature of these six cases was not found in time when the medical staff came to check the temperature on a twice-a-day basis. The system designed in this study, however, can detect the abnormal body temperature of all these six people. The sensitivity and specificity of our system were both 100%.

Conclusion The system designed in this study can monitor the body temperature, blood oxygen, blood pressure, heart rate, and geographical location of the monitoring subject in real time. It can be extended to COVID-19 medical observation isolation points, shelter hospitals, infectious disease wards, and nursing homes.

Keywords

Internet of Things - isolation - platform - vital sign monitoring


Publication History

Received: 06 April 2022

Accepted: 26 July 2022

Article published online:
15 November 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Li Q, Guan X, Wu P. et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med 2020; 382 (13) 1199-1207
    CrossrefPubMedGoogle Scholar
  • 2 National Health Commission of the People's Republic of China. Up to 24 May 20th novel coronavirus pneumonia epidemic situation, 2020. Accessed May 21, 2020 at: http://www.nhc.gov.cn/xcs/yqtb/202005/7be4e0b23c9441dcb9d0f6e6c0b1f4ae.shtml
    PubMedGoogle Scholar
  • 3 Liu S, Yang Y, Chen L. et al. Application of information technology in home quarantine of patients with sputum smear positive pulmonary tuberculosis. Zuo Wu Xue Bao 2018; 40 (09) 1012-1017
    PubMedGoogle Scholar
  • 4 Li Z, Xia K, He S. Design of the wearable device about body temperature detection based on wrist temperature measurement. Dianzi Celiang Jishu 2018; 41 (13) 100-106
    PubMedGoogle Scholar
  • 5 Lahiri BB, Bagavathiappan S, Jayakumar T, Philip J. Medical applications of infrared thermography: a review. Infrared Phys Technol 2012; 55 (04) 221-235
    CrossrefPubMedGoogle Scholar
  • 6 Zheng Y, Yu X. Wearable high-precision body temperature monitoring system. Digital Technology and Application 2016; 2: 219-221
    PubMedGoogle Scholar
  • 7 Molina J, Escudero-Viñolo M, Signoriello A. et al. Real-time user independent hand gesture recognition from time-of-flight camera video using static and dynamic models. Mach Vis Appl 2013; 24 (01) 187-204
    CrossrefPubMedGoogle Scholar
  • 8 Matos S, Birring SS, Pavord ID, Evans DH. Detection of cough signals in continuous audio recordings using hidden Markov models. IEEE Trans Biomed Eng 2006; 53 (06) 1078-1083
    CrossrefPubMedGoogle Scholar
  • 9 Li W, Chen R. Intelligent medical system based on the internet of things and strategy research of its construction. Laser J 2014; 35 (05) 56-58
    PubMedGoogle Scholar
  • 10 Jia Z, Wang W, Wang C. et al. Application and development of wearable sevices in medical field. China Medical Devices 2017; 32 (02) 96-99
    PubMedGoogle Scholar
  • 11 Cloud picture walk Website.. Isolation medical observation management system. Accessed May 10, 2020, at: http://cn.map20000.com/#/login
    PubMedGoogle Scholar
  • 12 Health Industry Standard of the People's Republic of China, WS/T 659–2019: Safety management for multi-parameter patient monitor
    PubMed
  • 13 Health industry standard of the People's Republic of China, YY0784–2010/ISO 9919–2005: Medical electrical equipment—particular requirements for basic safety and essential performance of pulse oximeter equipment for medical use
    PubMed
  • 14 National standard of the People's Republic of China, GB/T 21416–2008: Clinical electronic thermometer
    PubMed
  • 15 Yu C, Qu Z, Su J. et al. Design of wearable wrist-worn body temperature monitoring device. Transducer and Microsystem Technologies 2017; 36 (04) 121-127
    PubMedGoogle Scholar
  • 16 Chiappini E, Sollai S, Longhi R. et al. Performance of non-contact infrared thermometer for detecting febrile children in hospital and ambulatory settings. J Clin Nurs 2011; 20 (9–10): 1311-1318
    CrossrefPubMedGoogle Scholar
  • 17 Pei X, YU M, Cheng Q. et al. Detection and Identification of cough by belt-style multi-parameter physiological signals monitoring system. Chin Med Equip J 2014; 35 (04) 1-3
    PubMedGoogle Scholar
  • 18 Nsofor CA, Jiang Q, Wu J. et al. Transmission is a noticeable cause of resistance among treated tuberculosis patients in Shanghai, China. Sci Rep 2017; 7 (01) 7691
    CrossrefPubMedGoogle Scholar
  • 19 Lee MG, Undem BJ. Basic mechanisms of cough: current understanding and remaining questions. Lung 2008; 186 (1, Suppl 1): S10-S16
    CrossrefPubMedGoogle Scholar
  • 20 Tang L, Zhang J, Yu R. Research on detection system of cough sound based on wireless sensor networks. Transducer and Microsystem Technologies 2011; 30 (12) 25-27
    PubMedGoogle Scholar
  • 21 Yang G, Mo H, Li W, Lian L, Zheng Z. The endpoint detection of cough signal in continuous speech [in Chinese]. Sheng Wu I Hsueh Kung Cheng Hsueh Tsa Chih 2010; 27 (03) 544-547 , 555
    PubMedGoogle Scholar
  • 22 Gao S, Zhang W, Bai Z. et al. Microfiber-enabled in-line Fabry-Perot interferometer for high-sensitive force and refractive index sensing. J Lightwave Technol 2014; 32 (09) 1682-1688
    CrossrefPubMedGoogle Scholar
  • 23 Surabhi V, Spinello D, Necsulescu D. Infrared fever body identification using shape and temperature filters. Paper presented at: Proceeding of 2012 IEEE I2MTC-International Instrumentation and Measurement Technology Conference. Graz, Austria: IEEE; 2012: 1556-1560
    PubMedGoogle Scholar
  • 24 World Health Organization. Global Tuberculosis Report 2017. Geneva: World Health Organization; 2017: 212-262
    Google Scholar