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논문 기본 정보

자료유형
학술저널
저자정보
김동현 (한국기계연구원) 박해준 (한국기계연구원) 이창화 (영남대학교) 심성보 (한국기계연구원) 김철 (경북대학교) 서준호 (한국기계연구원)
저널정보
제어로봇시스템학회 제어로봇시스템학회 논문지 제어로봇시스템학회 논문지 제28권 제9호
발행연도
2022.9
수록면
804 - 810 (7page)
DOI
10.5302/J.ICROS.2022.22.0099

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이 논문의 연구 히스토리 (2)

초록· 키워드

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This study proposes a new assistive device that ensures consistency and improves safety in sample collection for detecting upper respiratory diseases such as COVID-19. The COVID-19 pandemic and the various mutations of the coronavirus have increased the demand for swab-sampling–based specimen collection. Currently, the most accurate method of collecting respiratory specimens is to insert a cotton swab through the nasal passage and touch the nasopharyngeal wall. Here, the success of sampling is subjectively determined by the force applied to the swab; test results may therefore vary based on the degree of training of the medical staff, and excess force can sometimes cause pain and aftereffects in patients. Therefore, we developed a device that measures the force applied to the swab when it is inserted up to the nasopharyngeal wall and indicates this to medical staff with an audiovisual signal. In this study, we introduce the details of the sample collection devices and validate the developed device through phantom model experiments. The results of five model experiments confirm that when both visual and auditory signals were given to medical staff, more consistent swab sampling was achieved than the conventional method without signals.

목차

Abstract
I. 서론
II. Methods
III. Experiments
IV. 고찰
V. 결론
REFERENCES

참고문헌 (19)

참고문헌 신청
W. Guan, Z. Ni, Yu Hu, W. Liang, C. Ou, J. He, L. Liu, H. Shan, C. Lei, D.S.C. Hui, B. Du, L. Li, G. Zeng, K.-Y. Yuen, R. Chen, C. Tang, T. Wang, P. Chen, J. Xiang, S. Li, Jin-lin Wang, Z. Liang, Y. Peng, L. Wei, Y. Liu, Ya-hua Hu, P. Peng, Jian-ming Wang, J. Liu, Z. Chen, G. Li, Z. Zheng, S. Qiu, J. Luo, C. Ye, S. Zhu, and N. Zhong, “Clinical characteristics of coronavirus disease 2019 in China,” The new england journal of medicine, vol. 382, no. 18, pp. 1708-1720, Feb. 2020, doi: 10.1056/nejmoa2002032. Crossref M. Yüce, E. Filiztekin, and K. G. Özkaya, “COVID-19 diagnosis-A review of current methods,” Biosens. Bioelectronics, vol. 172, no. Oct. 2020, 2021, doi: 10.1016/j.bios.2020.112752. Crossref A. H. Mohamed Ismail, M. A. Mohd Razman, I. Mohd Khairuddin, R. M. Musa, and A. P. P. Abdul Majeed, “The diagnosis of COVID-19 by means of transfer learning through X-ray images,” International Conference on Control, Automation and Systems, vol. 2021-Octob, no. Iccas, pp. 592-595, Oct. 2021, doi: 10.23919/ICCAS52745.2021.9649899. Crossref N. Sethuraman, S. S. Jeremiah, and A. Ryo, “Interpreting diagnostic tests for SARS-CoV-2,” JAMA The Journal of the American Medical Association, vol. 323, no. 22, pp. 2249-2251, Jun. 2020, doi: 10.1001/jama.2020.8259. Crossref W. Wang, Y. Xu, R. Gao, R. Lu, K. Han, G. Wu, and W. Tan, “Detection of SARS-CoV-2 in different types of clinical specimens,” JAMA The Journal of the American Medical Association, vol. 323, no. 11, pp. 1061-1069, May 2020, doi: 10.1001/jama.2020.1585. Crossref

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UCI(KEPA) : I410-ECN-0101-2022-003-001685000