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Methods for Noninvasive Determination of Blood Glucose Concentration Using Multisensor Systems

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Biomedical Engineering Aims and scope

An approach to achieving sufficiently accurate noninvasive determination of blood glucose concentration by combining noninvasive measurement methods is considered. Multisensor systems based on combinations of spectroscopic methods with impedance, thermal, ultrasonic, and other noninvasive methods are described. A review of modern approaches to calculating target values in a multisensor system for measuring glucose concentration based on machine learning methods and neural networks is presented.

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References

  1. Yeh, S. J., Hanna, C. F., and Khalil, O. S., "Monitoring blood glucose changes in cutaneous tissue by temperaturemodulated localized reflectance measurements," Clin. Chem., 49, 924–934 (2003).

    Article  CAS  PubMed  Google Scholar 

  2. Maruo, K., Tsurugi, M., Chin, J., Ota, T., Arimoto, H., Yamada, Y., Tamura, M., Ishii, M., and Ozaki, Y., "Noninvasive blood glucose assay using a newly developed near-infrared system," IEEE J. Select. Top. Quant. Electron., 9, 322–330 (2003).

    Article  CAS  Google Scholar 

  3. Schrader, W., Meuer, P., Popp, J., Kiefer, W., Menzebach, J. U., and Schrader, B., "Noninvasive glucose determination in the human eye," J. Mol. Str., 735, 736, 299–306 (2005).

    Article  Google Scholar 

  4. Kasemsumran, S., Du, Y., Maruo, K., and Ozaki, Y., "Improvement of partial least squares models for in vitro and in vivo glucose quantifications by using near-infrared spectroscopy and searching combination moving window partial least squares," Chemometrics Intell. Lab. Syst., 82, 97–103 (2006).

    Article  CAS  Google Scholar 

  5. Olesberg, J. T., Liu, L., Zee, V. V., and Arnold, V. A., "In vivo near-infrared spectroscopy of rat skin tissue with varying blood glucose levels," Anal. Chem., 78, No. 1, 11–20 (2004).

    Google Scholar 

  6. Pozhar, K. V., Litinskaia, E. L., Mikhailov, M. O., and Polyakova, E. A., "Near-infrared spectroscopy for noninvasive measurement of blood glucose: Problems, progress, tasks," Biomed. Eng., 56, No. 1, 64–68 (2022).

    Article  Google Scholar 

  7. Tronstad, Ch., Elvebakk, O., Staal, O. M., Kalvøy, H., Høgetveit, J. O., Jenssen, T. G., Birkeland, K. I., and Martinsen, Ø. G., "Non-invasive prediction of blood glucose trends during hypoglycemia," Analyt. Chim. Acta, 1052, 37–48 (2019).

    Article  CAS  Google Scholar 

  8. Nandi, S., Zhan, Y., Xia, A., Singh, T., and Mastrandrea, L., "A noninvasive glucose estimation based on near infrared spectroscopy and pulse-echo ultrasound," in: Proceedings of the 13th Russian German Conference on Biomedical Engineering (2018), pp. 90–93.

  9. Saetchnikov, V. A., Tcherniavskaia, E. A., and Schiffner, G., "Noninvasive glucose monitoring by optical reflective and thermal emission spectroscopic measurements," in: Novel Optical Instrumentation for Biomedical Applications II, 5864, 222–229 (2005).

    Google Scholar 

  10. Nguyen, D., Nguyen, H., and Roveda, J., "A non-invasive blood glucose meter design using multi-type sensors," in: Proc. SPIE Medical Applications of Radiation Detectors II, 8508 (2012).

  11. Feng, R., Geng, Z., Li, A., Chu, Y., Wu, C., Zhang, N., Guo, X., Zhang, J., Wang, X., and Tang, F., "Noninvasive blood glucose monitor via multi-sensor fusion and its clinical evaluation," Sensors and Actuators B: Chemical, 332, Article ID 129445 (2021).

  12. Caduff, A., Talary, M. S., Mueller, M., Dewarrat, F., Klisic, J., Donath, M., Heinemann, L., and Stahel, W. A., "Noninvasive glucose monitoring in patients with Type 1 diabetes: A multisensor system combining sensors for dielectric and optical characterisation of skin," Biosens. Bioelectron., 24, No. 9, 2778–2784 (2009).

    Article  CAS  PubMed  Google Scholar 

  13. Harman-Boehm, I., Gal, A., Raykhman, A. M., Naidis, E., and Mayzel, Y., "Noninvasive glucose monitoring: increasing accuracy by combination of multi-technology and multi-sensors," J. Diabetes Sci. Technol., 4, No. 3, 583–595 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Song, K., Ha, U., Park, S., Bae, J., and Yoo, H.-J., "An impedance and multi-wavelength near-infrared spectroscopy IC for non-invasive blood glucose estimation," IEEE J. Solid-State Circuits, 50, No. 4, 1025–1037 (2015).

    Article  Google Scholar 

  15. Guevara, E. and González, F. J., "Joint optical-electrical technique for noninvasive glucose monitoring," Revista Mexicana de Física, 56, No. 5, 430–434 (2010).

    CAS  Google Scholar 

  16. Abd El Ghany, M. A., "Notice of Retraction: High performance non-invasive glucose monitoring system," in: 2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST) (2020).

  17. Fouad, M. M., Mahmoud, D. Y., and Abd El Ghany, M. A., "Joint NIR-BIS based non-invasive glucose monitoring system," in: 2018 30th International Conference on Microelectronics (ICM) (2018), pp. 88–91.

  18. Asaduzzaman, A., Samadarsinee, S., and Chidella, K. K., "Simulating multisensor noninvasive blood glucose monitoring systems," in: SoutheastCon 2016 (2016).

  19. De Jong, S., "SIMPLS: An alternative approach to partial least squares regression," Chemometrics Intell. Lab. Syst., 18, No. 3, 251–263 (1993).

    Article  Google Scholar 

  20. Tarumi, M., Shimada, M., Murakami, T., Tamura, M., Shimada, M., Arimoto, H., and Yamada, Y., "Simulation study of in vitro glucose measurement by NIR spectroscopy and a method of error reduction," Phys. Med. Biol., 48, No. 15, 2373–2390 (2003).

    Article  CAS  PubMed  Google Scholar 

  21. Zanon, M., Sparacino, G., Facchinetti, A., Riz, M., Talary, M. S., Suri, R. E., Caduff, A., and Cobelli, C., "Non-invasive continuous glucose monitoring: Improved accuracy of point and trend estimates of the Multisensor system," Med. Biol. Eng. Comput., 50, 1047–1057 (2012).

    Article  PubMed  Google Scholar 

  22. Zanon, M., Sparacino, G., Facchinetti, A., Talary, M. S., Caduff, A., and Cobelli, C., "Regularised model identification improves accuracy of multisensor systems for noninvasive continuous glucose monitoring in diabetes management," J. Appl. Math., 2020, Article ID 9628281 (2020).

  23. Zeng, B., Wang, W., Wang, N., Li, F., Zhai, F., and Hu, L., "Noninvasive blood glucose monitoring system based on distributed multi-sensors information fusion of multiwavelength NIR," Engineering, 5, No. 10B, 553–560 (2013).

    Article  Google Scholar 

  24. Wang, W., Yan, L., Liu, B., and Zhang, H., "Multisensors information fusion with neural networks for noninvasive blood glucose detection." in: Advances in Neural Networks — ISNN 2005: Second International Symposium on Neural Networks, Chongqing, China, May 30–June 1, 2005. Proceedings, Springer, Berlin, Heidelberg (2005), pp. 760–766

  25. Amaral, C. F., Brischwein, M., and Wolf, B., "Multiparameter techniques for non-invasive measurement of blood glucose," Sensors and Actuators B: Chemical, 140, No. 1, 12–16 (2009).

    Article  CAS  Google Scholar 

  26. Yadav, J., Rani, A., Singh, V., and Mohan Murari, B., "Investigations on multisensor-based noninvasive blood glucose measurement system," J. Med. Devices, 11, No. 3, Article ID 031006 (2017).

  27. Jintao, X., Liming, Y., Yufei, L., Chunyan, L., and Han, C., "Noninvasive and fast measurement of blood glucose in vivo by near infrared (NIR) spectroscopy," Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 179, 250–254 (2017).

    Article  PubMed  Google Scholar 

  28. Zhang, Y., Zhu, J., Liang, Y., Chen, H., Yin, S., and Chen, Z., "Non-invasive blood glucose detection system based on conservation of energy method," Physiol. Meas., 38, No. 2, 325–342 (2017).

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Institute of Biomedical Systems, National Research University of Electronic Technology, Moscow, Russia

    M. O. Mikhailov & K. V. Pozhar

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  1. M. O. Mikhailov
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  2. K. V. Pozhar
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Correspondence to M. O. Mikhailov.

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Translated from Meditsinskaya Tekhnika, Vol. 57, No. 2, March–April, 2023, pp. 32–36.

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Mikhailov, M.O., Pozhar, K.V. Methods for Noninvasive Determination of Blood Glucose Concentration Using Multisensor Systems. Biomed Eng 57, 121–126 (2023). https://doi.org/10.1007/s10527-023-10282-y

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  • DOI: https://doi.org/10.1007/s10527-023-10282-y

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