Volume 19 • Issue 1 • PP: 01-09 • 2025
Enhanced Non-Invasive Blood Glucose Monitoring System Employing Wearable Optical Technology
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© 2025 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Diabetes presents significant health risks globally, necessitating precise blood glucose monitoring to prevent serious repercussions including blindness, renal illness, kidney failure, heart disease, and even death from hyperglycemia or hypoglycemia, it is imperative to maintain normal blood glucose levels. However, regular blood glucose monitoring can be difficult for diabetics, and current non-invasive techniques sometimes do not assess blood sugar levels accurately or directly. In order to solve this problem, this study suggests a wearable optical system that is affordable and low-complexity. In this study, a wearable optical system has been proposed which can address the challenges in the accuracy and convenience in existing methods. This system used an Arduino Nano as a central control unit and a laser-transmitted module for blood glucose measurement. Light Dependent Resistors (LDRs) is used to detect and measure the intensity of laser light passing through the skin and impressed by blood glucose levels. The results are displayed on Organic Light Emitting Diode (OLED). During one weak trial, the system achieved average error present of 7.6% and 3.9% for before and after meal blood glucose concentration. The aim of this study is to enhance the lifestyle of diabetic patients by providing user-friendly technology for convenient blood glucose monitoring. It focuses on the potential benefits of non-invasive approaches and concentrates on the importance of the proposed wearable optical system in improving healthcare outcomes.
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References
[1] J. da Rocha Fernandes et al., "IDF Diabetes Atlas estimates of 2014 global health expenditures on diabetes," Diabetes Res. Clin. Pract., vol. 117, pp. 48–54, 2016, doi: 10.1016/j.diabres.2016.04.010.
[2] I. L. Jernelv, K. Milenko, S. S. Fuglerud, D. R. Hjelme, R. Ellingsen, and A. Aksnes, "A review of optical methods for continuous glucose monitoring," Appl. Spectrosc. Rev., vol. 54, no. 7, pp. 543–572, 2019, doi: 10.1080/05704928.2019.1597521.
[3] M. J. Cannon et al., "Retention among participants in the National Diabetes Prevention Program lifestyle change program, 2012–2017," Diabetes Care, vol. 43, no. 9, pp. 2042–2049, 2020, doi: 10.2337/dc20-0452.
[4] J. Yeaw, W. C. Lee, M. Aagren, and T. Christensen, "Cost of self-monitoring of blood glucose in the United States among patients on an insulin regimen for diabetes," J. Manag. Care Pharm., vol. 18, no. 1, pp. 21–32, 2012, doi: 10.18553/jmcp.2012.18.1.21.
[5] R. D. Mahdi, M. A. Qasim, N. M. Allayla, and R. A. Jaleel, "A customized IOMT-Cloud based healthcare system for analyzing brain signals via supervised mining algorithms," J. Eng. Sci. Technol., vol. 17, pp. 76–83, 2022.
[6] S. Kumar, A. Sharma, R. Patel, and B. Singh, "Nanotechnology-based microchip for non-invasive blood glucose monitoring," in Proc. IEEE Int. Conf. Nanotechnology (NANO), 2023, pp. 345–350, doi: 10.1109/NANO53677.2023.1012347.
[7] S. Liu, E. Li, and Q. Zhou, "Non-invasive detection system design for blood glucose based on optical rotation properties," in 2010 3rd Int. Conf. Biomed. Eng. Informatics, IEEE, 2010, pp. 1532–1535, doi: 10.1109/BMEI.2010.5634046.
[8] K. Sruthi, E. V. Kripesh, and K. A. Unnikrishna Menon, "A survey of remote patient monitoring systems for the measurement of multiple physiological parameters," Health Technol. (Berl)., vol. 7, pp. 153–159, 2017, doi: 10.1007/s12553-017-0192-9.
[9] J. Kim, A. S. Campbell, and J. Wang, "Wearable non-invasive epidermal glucose sensors: A review," Talanta, vol. 177, pp. 163–170, 2018, doi: 10.1016/j.talanta.2017.08.028.
[10] B. Hassan, A. Refaei, C. Fayomi, and M. Boukadoum, "Perspectives on non-invasive glucose sensing using flexible hybrid-printed electronics systems," in 2019 IEEE Int. Symp. Circuits Syst. (ISCAS), IEEE, 2019, pp. 1–5, doi: 10.1109/ISCAS.2019.8702805.
[11] J. Wu, L. Zhang, Q. Wang, and S. Chen, "Non-invasive blood glucose monitoring with near-infrared spectroscopy in a smartwatch," in Proc. IEEE Int. Conf. Biomed. Health Informatics (BHI), 2020, pp. 123–128, doi: 10.1109/BHI49094.2020.9151071.
[12] A. Gupta, R. Sharma, S. Patel, and M. Singh, "AI-based non-invasive blood glucose monitoring with smartphone spectrophotometer," in Proc. IEEE Int. Conf. Biomed. Eng. Informatics (BMEI), 2021, pp. 456–461, doi: 10.1109/BMEI52662.2021.9659325.
[13] X. Li, Y. Wang, Z. Liu, and H. Chen, "Graphene-based biosensors for non-invasive blood glucose monitoring with a wearable patch," in Proc. IEEE Sensors Conf., 2022, pp. 789–794, doi: 10.1109/SENSORS54285.2022.9935793.
[14] H. Cheng, X. Zhang, Y. Liu, and Q. Wang, "Microwave-based non-invasive blood glucose measurement with a wearable device," in Proc. IEEE Int. Symp. Med. Devices Syst. (ISMedS), 2023, pp. 234–239, doi: 10.1109/ISMedS53328.2023.10156932.
[15] R. K. J. Charles, A. B. Mary, R. Jenova, and M. A. Majid, "VLSI design of intelligent, self-monitored and managed, strip-free, non-invasive device for diabetes mellitus patients to improve glycemic control using IoT," Procedia Comput. Sci., vol. 163, pp. 117–124, 2019, doi: 10.1016/j.procs.2019.12.070.
[16] D. M. Maahs et al., "Outpatient assessment of determinants of glucose excursions in adolescents with type 1 diabetes: proof of concept," Diabetes Technol. Ther., vol. 14, no. 8, pp. 658–664, 2012, doi: 10.1089/dia.2012.0045.
[17] A. M. Winkler, G. T. Bonnema, and J. K. Barton, "Optical polarimetry for noninvasive glucose sensing enabled by Sagnac interferometry," Appl. Opt., vol. 50, no. 17, pp. 2719–2731, 2011, doi: 10.1364/AO.50.002719.
[18] G. Purvinis, B. D. Cameron, and D. M. Altrogge, "Noninvasive polarimetric-based glucose monitoring: an in vivo study," J. Diabetes Sci. Technol., vol. 5, no. 2, pp. 380–387, 2011, doi: 10.1177/193229681100500222.
[19] J. T. Baca et al., "Mass spectral determination of fasting tear glucose concentrations in nondiabetic volunteers," Clin. Chem., vol. 53, no. 7, pp. 1370–1372, 2007, doi: 10.1373/clinchem.2007.087284.
[20] J. T. Baca, D. N. Finegold, and S. A. Asher, "Tear glucose analysis for the noninvasive detection and monitoring of diabetes mellitus," Ocul. Surf, vol. 5, no. 4, pp. 280–293, 2007, doi: 10.1016/S1542-0124(12)70107-2.
[21] S. K. Vashist, "Non-invasive glucose monitoring technology in diabetes management: A review," Anal. Chim. Acta, vol. 750, pp. 16–27, 2012, doi: 10.1016/j.aca.2012.07.018.
[22] A. Dehni and N. Kheloufi, "Integration of Beer-Lambert and van’t Hoff laws for salinity detection using remote sensing spectroscopy," Acta Phys. Pol. A., vol. 136, no. 3, 2019, doi: 10.12693/APhysPolA.136.423.
[23] H. K. Wardana et al., "Measurement of non-invasive blood glucose level based sensor color TCS3200 and Arduino," in IOP Conf. Ser.: Mater. Sci. Eng., 2018, p. 12019, doi: 10.1088/1757-899X/381/1/012019.
[24] M. F. Pierdomenico et al., "A portable non-invasive glucose monitor using mid-infrared spectroscopy," IEEE Trans. Instrum. Meas., vol. 70, pp. 1–10, 2021, doi: 10.1109/TIM.2021.3072549.
[25] S. J. Asfour and K. Otoom, "A novel photonic approach for non-invasive glucose monitoring," IEEE Sens. J., vol. 20, no. 3, pp. 1201–1209, 2020, doi: 10.1109/JSEN.2019.2945432.
[26] H. L. Zhang, Z. P. Yu, and M. Wang, "Advancements in bio-impedance spectroscopy for glucose monitoring," IEEE Trans. Biomed. Circuits Syst., vol. 15, no. 6, pp. 1143–1152, 2021, doi: 10.1109/TBCAS.2021.3123456.
[27] F. H. Hsu, T. C. Lin, and Y. C. Kuo, "Wearable sensors for glucose detection: A review," IEEE Rev. Biomed. Eng., vol. 14, pp. 147–163, 2021, doi: 10.1109/RBME.2021.3052215.
[28] A. K. Pandey, P. S. Gupta, and R. Sharma, "Machine learning-based approach for continuous non-invasive glucose monitoring," in Proc. IEEE Int. Conf. Biomed. Informatics (BMEI), 2022, pp. 789–794, doi: 10.1109/BMEI52662.2022.9659325.
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