DOI QR코드

DOI QR Code

근적외선 분광법 기반 비침습식 혈당 검출 센서 시스템

Non-invasive Blood Glucose Detection Sensor System Based on Near-Infrared Spectroscopy

  • 강영만 (전남대학교 문화콘텐츠학부) ;
  • 한순희 (전남대학교 문화콘텐츠학부)
  • 투고 : 2021.07.22
  • 심사 : 2021.10.17
  • 발행 : 2021.10.31

초록

비침습식 혈당 검출 기술 중 광학 기법은 생물학적 매체를 통과할 때 빛의 반사와 흡수 및 산란 특성을 이용하는 방법으로 통증이나 측정의 불편함을 감소시키고 감염 위험이 없어 혈당 검출 연구의 주요 흐름이 되고 있다. 이 중 근적외선 분광법은 혈당 분자와 유사한 흡수 기능을 공유하는 단백질과 산의 간섭들로 감지된 신호 분석 시 복잡성이 증가하는 단점이 있다. 본 연구에서는 근적외선의 피부 흡수로 발생할 수 있는 혈당검출 기능저하를 완화시키기 위해 다중 근적외선 대역의 비침습식 센서시스템을 설계하고 제작하였다. 제작한 시스템의 검증을 위해 혈액 조사를 실시하였으며, 혈액 내의 혈당 반응 정도를 스펙트럼 데이터로 수집하고, 데이터와 혈당과의 상관관계 관점에서 정량적으로 본 연구의 성과를 검증하였다.

Among non-invasive blood glucose detection technologies, the optical technique is a method that uses light reflection, absorption, and scattering characteristics when passing through a biological medium. It reduces pain or discomfort in measurement and has no risk of infection. So it is becoming a major flow of blood glucose detection research. Among them, near-infrared spectroscopy has a disadvantage in that the complexity increases when analyzing signals detected due to interferences between proteins and acids that share a similar absorption function with blood glucose molecules. In this study, a non-invasive sensor system with multiple near-infrared bands was designed and manufactured to alleviate the deterioration of blood glucose detection function that may occur due to skin absorption of near-infrared rays. A blood survey was conducted to verify the system, and the degree of blood glucose response in the blood was collected as spectral data, and the results of this study were quantitatively verified in terms of correlation between the data and blood glucose.

키워드

참고문헌

  1. C. E. F. do Amaral and B. Wolf, "Current development in non-invasive glucose monitoring," Medical Engineering & Physics, vol. 30, no. 5, 2008, pp. 541-549. https://doi.org/10.1016/j.medengphy.2007.06.003
  2. S. Hong, "Design and Implementation of Healthcare System Based on Non-Contact Biosignal Measurement," Journal of the Korea institute of electronic communication sciences, vol. 15, no. 1, 2020, pp. 185-190. https://doi.org/10.13067/JKIECS.2020.15.1.185
  3. H. Lee and J. Oh, "Design and Implementation of Non-contact IoT Ringer Replacement Automatic Notification System," Journal of the Korea institute of electronic communication sciences, vol. 13, no. 6, 2018, pp. 1405-1410. https://doi.org/10.13067/JKIECS.2018.13.6.1405
  4. W. Ahn and J. Kim, "Blood Glucose Measurement Principles of Non-invasive Blood Glucose Meter: Focused on the Detection Methods of Blood Glucose," Journal of Biomedical Engineering Research, no. 33, 2012, pp. 114-127.
  5. S. Yeh, C. F. Hanna, and O. S. Khalil, "Monitoring blood glucose changes in cutaneous tissue by temperature-modulated localized reflectance measurements," Clinical Chemistry, vol. 49, no. 6, 2003, pp. 924-934. https://doi.org/10.1373/49.6.924
  6. W. Schrader, P. Meuer, J. Popp, W. Kiefer, J.-U. Menzebach, and B. Schrader, "Non-invasive glucose determination in the human eye," J. of Molecular Structure, vol. 735-736, 2005, pp. 299-306. https://doi.org/10.1016/j.molstruc.2004.10.115
  7. J. T. Olesberg, L. Liu, V. V. Zee, and M. A. Arnold, "In vivo near-infrared spectroscopy of rat skin tissue with varying blood glucose levels," Analytical Chemistry, vol. 78, no. 1, 2006, pp. 215-223. https://doi.org/10.1021/ac051036i
  8. A. Nawaz, P. Ohlckers, S. Saelid, M. Jacobsen, and M. N. Akram, "Review: non-invasive continuous blood glucose measurement techniques," J. of Bioinformatics and Diabetes, vol. 1, no. 3, 2016, pp. 1-27. https://doi.org/10.14302/issn.2374-9431.jbd-15-647
  9. M. A. Arnold and G. W. Small, "Noninvasive glucose sensing," Analytical Chemistry, vol. 77, no. 17, 2005, pp. 5429-5439. https://doi.org/10.1021/ac050429e
  10. N. S. Oliver, C. Toumazou, A. E. G. Cass, and D. G. Johnston, "Glucose sensors: a review of current and emerging technology," Diabet. Med: j. of the british diabetic association, vol. 26, no. 3, Mar. 2009, pp. 197-210. https://doi.org/10.1111/j.1464-5491.2008.02642.x
  11. K. Maruo, T. Oota, M. Tsurugi, T. Nakagawa, H. Arimoto, M. Tamura, Y. Ozaki, and Y. Yamada, "New Methodology to Obtain a Calibration Model for Noninvasive Near-Infrared Blood Glucose Monitoring," j. of Applied Spectroscopy, vol. 60, no. 4, Apr. 2006, pp. 441-449. https://doi.org/10.1366/000370206776593780
  12. P. Avci, A. Gupta, M. Gupta, D. Vecchio, Z. Pam, N. Pam, and M. R. Hamblin, "Low-level laser (light) therapy (LLLT) in skin: Stimulating, healing, restoring," Semin. Cutan. Med. Surg, vol. 32, no. 1, 2013, pp. 41-52.
  13. C. Ash, M. Dubec, K. Donne, and T. Bashford, "Effect of wavelength and beam width on penetration in light-tissue interaction using computational methods," Lasers in Medical Science, vol. 32, 2017, pp. 1909-1918. https://doi.org/10.1007/s10103-017-2317-4
  14. S. Chatterjee and P. A. Kyriacou, "Monte Carlo Analysis of Optical Interactions in Reflectance and Transmittance Finger Photoplethysmography," Research Centre for Biomedical Engineering, vol. 19, no. 4, 2019, pp. 789.
  15. A. Savitzky and M. J. E. Golay, "Smoothing and Differentiation of Data by Simplified Least Squares Procedures," Analytical Chemistry, vol. 36, no. 8, 1964, pp. 1627-1639. https://doi.org/10.1021/ac60214a047
  16. A. Savitzky, "A Historic Collaboration," Analytical Chemistry, vol. 61, no. 15, Aug. 1989, pp. 921A-923A. https://doi.org/10.1021/ac00190a744
  17. W. Kirch, Encyclopedia of Public Health - Pearson's Correlation Coefficient. Dordrecht: Springer, 2008.