Journal of Industrial Convergence (산업융합연구)

DAEHAN Society of Industrial Management (대한산업경영학회)
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A Study on the Disease Prevention Monitoring System Using IoMT Environment

IoMT 환경을 이용한 질병 예방 모니터링 시스템에 관한 연구

  • Sung-Ho, Sim (College of General Education, Semyung University)
  • Received : 2022.12.28
  • Accepted : 2023.02.20
  • Published : 2023.02.28
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Abstract

Recently, viral infectious diseases and new diseases are not limited to one region, but are spreading worldwide, causing serious economic and social damage. In addition, the development cycle of new diseases is shortening, and the rate of spread is accelerating. In order to prevent the spread of disease, passive forms of response after a disease outbreak, such as personal and regional quarantine and border closure, are prioritized. This type of response has many shortcomings as a fundamental response to preventing the spread of disease. Therefore, this study proposes a disease prevention monitoring system including new disease occurrence information. In this study, disease information and user information are collected through the establishment of the IoMT environment. Information collection using an agent collects and classifies data registered in the disease information server. In the IoMT environment, user data is collected, and whether the user is infected with a disease is evaluated and provided to the user. Through this study, individual disease symptom information can be provided and active countermeasures against the spread of disease can be provided.

최근 바이러스 감염병 및 새로운 질병은 한 지역에 국한되는 것이 아니라 전 세계적으로 확산되어 경제적, 사회적으로 심각한 피해를 일으키고 있다. 또한, 새로운 질병의 발현 주기가 짧고, 확산 속도도 빨라지고 있다. 질병에 대한 확산을 막기 위해 격리, 폐쇄 등 질병 발생 후 수동적인 형태의 대응이 우선시 되고 있다. 이러한 형태의 대응은 질병 확산 방지에 근본적인 대응으로는 부족한 부분이 많이 있다. 이에, 본 연구에서는 새로운 질병 발생 정보를 포함한 질병 예방 모니터링 시스템을 제안한다. 본 연구에서는 IoMT 환경 구축을 통해 질병 정보와 사용자의 정보를 수집한다. devices를 이용한 정보 수집은 사용자의 생체정보와 질병 서버에 등록된 데이터를 수집하고 분류한다. IoMT 환경에서는 사용자의 데이터를 수집하여 사용자 질병 감염 여부를 평가하여 사용자에게 제공한다. 본 연구를 통해 개인의 질병 증상 정보를 제공하고, 질병 확산에 대한 능동적인 대응 방법을 제공할 수 있다.

Keywords

Acknowledgement

This paper was supported by Semyung University research fund in 2022.

References

  1. L. Hawryluck, W. L. Gold, S. Robinson, S. Pogorski, S. Galea & R. Styra. (2004). SARS control and psycholgical effects of quarantine. Emerging Infectious Diseases, 10(7), 1206-1212. https://doi.org/10.3201/eid1007.030703
  2. C. Benke, L. K. Autenrieth, E. Asselmann & C. A. Pane-Farre. (2020). Lockdown, quarantine meassures, and social distancing: Associations with depression, anciety and distress at the beginning of the COCID-19 pandemic among adults from Germany. Psychiatry research, 293, 113462.
  3. L. Ferretti, C. Wymant, M. Kendall, L. Nurtay, A. Nurtay, L. Abeler-Dorner, ...& C. Fraser. (2020). Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science, 368(6491), eabb6936. DOI : 10.1126/science.abb6936
  4. M. Abueg, R. Hinch, N. Wu, L. Lin, W. Probert, A.Wu, ...& C. Fraser. (2021). Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in Washington state. NPJ digital medicine, 4(1), 1-10. https://doi.org/10.1038/s41746-020-00373-5
  5. F. Tang, J. Liang, H. Zhang, M. M. Kelifa, Q. He & P. Wang. (2020). COVID-19 related depression and anxiety among quarantined respondents. psychology&health, 36(2), 164.178.
  6. M. W. Fong, H. Gao, J. Y. Wong, J. Wong Y. Shiu, S. Ryu & B. J. Cowling. (2020). Nonpharmaceutical measures for pandemic influenza in nonhealthcare settings-social distancing measures. Emerging infectious diseases, 26(5), 976.
  7. S. K. Brooks, R. K. Webster. L. E. Smith, L. Woodland, S. Wessely, N. Greenberg & G. J. Rubin. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. The lancet, 395(10227), 912-920. DOI : 10.1016/S0140-6736(20)30460-8
  8. D. B. KIM. (2021). Ethical Concerns Regarding Patient Autonomy at a COVID-19 Residential Treatment Center. Korean J Med Ethics 24(1), 81-87. https://doi.org/10.35301/KSME.2021.24.1.81
  9. S. Hwang & S. H. Sun. (2021). A Study on a Wearable Device for Monitoring Biosignals of a Patch Type for Quarantined Persons. Journal of Industrial Design Studies, 15(4), 51-63. https://doi.org/10.37254/ids.2021.12.58.04.51
  10. E. Kang, S.. Y. Lee, M. S. Kim, H. Jung, K. H. Kim, K. N. Kim.,...& J. H. Sohn. (2021). The psychological burden of COVID-19 stigma: evaluation of the mental health of isolated mild condition COVID-19 patients. Journal of Korean medical science, 36(3).
  11. Internet of Things(IoT): Number of Connected Devices Worldwide From 2012 to 2020(in billions). [Online].
  12. H. J. Mun. (2022). Research of DID-vased Verification System in the Blockchain Technology. Journal of Consulting Convergence research, 2(1), 9-14. DOI : 10.55479/JCCR.2022.2.1.009
  13. F. Andriopoulou, T. Dagiuklas & T. Orphanoudakis. (2017). Integrating IoT and fog computing for healthcare service delivery. In Components and services for IoT platforms, 213-232.
  14. G. J. Joyia, R. M. Liaqat, A. Farooq & S. Rehman. (2017). Internet of medical things (IoMT): Applications, benefits and future challenges in healthcare domain. J. Commun, 12(4), 240-247.
  15. W. M. de Souza, L. F. Buss, D. Candido, J. P. Carrera, S. Li, A. Zarebski,... & N.R. Faria. (2020). Epidemiological and clinical characteristics of the early phase of the COVID-19 epidemic in Brazil. medRxiv.
  16. R. P. Singh, M. Javaid, A. Haleem & R. Suman. (2020). Internet of things (IoT) applications to fight against COVID-19 pandemic. Diabetes & Metavolic Syndrome: Clinical Research & Reviews, 14(4), 521-524. DOI : 10.1016/j.dsx.2020.04.041
  17. N. Chen, M. Zhou, X. Dong, J. Qu, F. Gong, Y. Han, ...& L. Zhang. (2020). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The lancet, 395(10223), 507-513. DOI : 10.1016/S0140-6736(20)30211-7
  18. K. H. Lee. (2015). Emergency medical services in response to the middle east respiratory syndrome out break in Korea. J Korean Med Assoc, 58(7), 611-616
  19. M. D. Oh. (2016). The Korean Middle East respiratory syndrome coronavirus out break and outbreak and our responsibility to the global scientific community. Infection & chemotherapy, 48(2), 145-146. https://doi.org/10.3947/ic.2016.48.2.145
  20. L. S. Meredith, D. P. Eisenman, T. Tanielian, S. L. Taylor, R. Basurto-Davila, J. Zazzali, ...& S. Shields. (2011). Prioritizing "psychological" consequences for disaster preparedness and response: a framework for addressing the emotional, behavioral, and cognitive effects of patient surge in large-scale disasters. Disaster medicine and public health preparedness, 5(1), 73-80. https://doi.org/10.1001/dmp.2010.47
  21. G. Pappas, I. J. Kiriaza, P. Giannakis & M. E. Falagas. (2009). Psychosocial consequences of infectious diseases. Clinical microbiology and infection, 15(8), 743-747 https://doi.org/10.1111/j.1469-0691.2009.02947.x
  22. H. Y. Park. (2021). Mental Health in Patients with Coronavirus Disease-19 and the Quarantined People. J Korean Neuropsychiatr Assoc, 60(1), 11-18. DOI : 10.4306/jknpa.2021.60.1.11
  23. N. K. Kim, C.H. Lee, J. S. Oh & S. R. Cho. (2020). A study on IoMT and a survey on the IoMT-based edge computing studies. Proceedings of Symposium of the Korean Institute of communications and Information Science, 928-929.
  24. D. V. Dimitrov. (2016). Medical internet of things and big data in healthcare. Healthcare informatics research, 22(3), 156-163. https://doi.org/10.4258/hir.2016.22.3.156