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Cited by 772

The DOI matches its Crossref record; 130 of the 130 references it cites were found in a registry or an index.

The Progress of Glucose Monitoring—A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors

Open access
Villena Gonzales, Wilbert, Mobashsher, Ahmed, Abbosh, Amin·2019·Sensors
DOI 10.3390/s19040800
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Abstract

Current glucose monitoring methods for the ever-increasing number of diabetic people around the world are invasive, painful, time-consuming, and a constant burden for the household budget. The non-invasive glucose monitoring technology overcomes these limitations, for which this topic is significantly being researched and represents an exciting and highly sought after market for many companies. This review aims to offer an up-to-date report on the leading technologies for non-invasive (NI) and minimally-invasive (MI) glucose monitoring sensors, devices currently available in the market, regulatory framework for accuracy assessment, new approaches currently under study by representative groups and developers, and algorithm types for signal enhancement and value prediction. The review also discusses the future trend of glucose detection by analyzing the usage of the different bands in the electromagnetic spectrum. The review concludes that the adoption and use of new technologies for glucose detection is unavoidable and closer to become a reality.

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Citations

Cites

Show all 130 references

Research works printed but not linked: 26

  1. Chakraborty, P.P., Patra, S., Bhattacharjee, R., and Chowdhury, S. (2017). Erroneously elevated glucose values due to maltose interference in mutant glucose dehydrogenase pyrroloquinolinequinone (mutant GDH-PQQ) based glucometer. BMJ Case Rep. · doi:10.1136/bcr-2017-219928
  2. China Food & Drug Administration (CFDA) (2016). Glucometer Registration Technical Review Guidelines.
  3. Jia, 2008, Carbon Nanotubes Based Glucose Needle-type Biosensor, Sensors, 8, 1712, 10.3390/s8031712 · doi:10.3390/s8031712
  4. Peng, H., Li, Q., and Chen, T. (2017). Chapter 5–Carbon Nanotubes for Sensing Applications. Industrial Applications of Carbon Nanotubes, Elsevier.
  5. Li, D.C., Wu, J.W., Wu, P., Lin, Y., Sun, Y.J., Zhu, R., Yang, J., and Xu, K.X. (2015, January 21–25). Glucose measurement using surface plasmon resonance sensor with affinity based surface modification by borate polymer. Proceedings of the 2015 Transducers-2015 18th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), Anchorage, AK, USA. · doi:10.1109/transducers.2015.7181238
  6. Bambot, 1995, Sensing oxygen through skin using a red diode laser and fluorescence lifetimes, Biosens. Bioelectron., 10, 643, 10.1016/0956-5663(95)96941-Q · doi:10.1016/0956-5663(95)96941-q
  7. Malik, 2010, Real-time, closed-loop dual-wavelength optical polarimetry for glucose monitoring, J. Biomed. Opt., 15, 017002, 10.1117/1.3290819 · doi:10.1117/1.3290819
  8. Coates, 1998, Vibrational Spectroscopy: Instrumentation for Infrared and Raman Spectroscopy, Appl. Spectr. Rev., 33, 267, 10.1080/05704929808002060 · doi:10.1080/05704929808002060
  9. Xhelaj, 2005, A novel approach to non-invasive glucose measurement by mid-infrared spectroscopy: The combination of quantum cascade lasers (QCL) and photoacoustic detection, Vib. Spectr., 38, 209, 10.1016/j.vibspec.2005.02.025 · doi:10.1016/j.vibspec.2005.02.025
  10. Alarousu, E., Hast, J.T., Kinnunen, M.T., Kirillin, M.Y., Myllyla, R.A., Plucinski, J., Popov, A.P., Priezzhev, A.V., Prykari, T., and Saarela, J. (2003, January 7–10). Noninvasive glucose sensing in scattering media using OCT, PAS, and TOF techniques. Proceedings of the Saratov Fall Meeting 2003: Optical Technologies Biophysics and Medicine V, Saratov, Russia. · doi:10.1117/12.578321
  11. Gusev, S.I., Guseva, V.A., Simonova, A.A., Demchenko, P.S., Sedykh, E.A., Cherkasova, O.P., and Khodzitsky, M.K. (2017, January 22–25). Application of terahertz pulsed spectroscopy for the development of non-invasive glucose measuring method. Proceedings of the 2017 Progress In Electromagnetics Research Symposium-Spring (PIERS), St Petersburg, Russia. · doi:10.1109/piers.2017.8262313
  12. Buchert, 2004, Thermal emission spectroscopy as a tool for noninvasive blood glucose measurements, Proc. SPIE, 5566, 100, 10.1117/12.577219 · doi:10.1117/12.577219
  13. Tang, 2008, Non-Invasive Glucose Measurement by Use of Metabolic Heat Conformation Method, Sensors, 8, 3335, 10.3390/s8053335 · doi:10.3390/s8053335
  14. Sandeep, K.V., and Luong, J.H.T. (2016). Point-of-Care Glucose Detection for Diabetic Monitoring and Management, CRC Press. [1st ed.].
  15. Patel, 2013, A Review on Photoacoustic Spectroscopy, Int. J. Pharm. Erud., 3, 41
  16. Tanaka, Y., Tajima, T., and Seyama, M. (2018, January 19). Differential photoacoustic spectroscopy with continuous wave lasers for non-invasive blood glucose monitoring. Proceedings of the Photons Plus Ultrasound: Imaging and Sensing 2018, San Francisco, CA, USA. · doi:10.1117/12.2287039
  17. Nakamura, M., Tajima, T., Ajito, K., and Koizumi, H. (2016, January 22–27). Selectivity-enhanced glucose measurement in multicomponent aqueous solution by broadband dielectric spectroscopy. Proceedings of the 2016 IEEE MTT-S International Microwave Symposium (IMS), San Francisco, CA, USA. · doi:10.1109/mwsym.2016.7540257
  18. Bahar, A.A.M., Zakaria, Z., Isa, A.A.M., Alahnomi, R.A., and Rahman, N.A. (2018, January 19–22). Complex Permittivity Measurement Based on Planar Microfluidic Resonator Sensor. Proceedings of the 2018 18th International Symposium on Antenna Technology and Applied Electromagnetics (ANTEM), Waterloo, ON, Canada. · doi:10.1109/antem.2018.8572934
  19. Hofmann, M., Fersch, T., Weigel, R., Fischer, G., and Kissinger, D. (2011, January 30–31). A novel approach to non-invasive blood glucose measurement based on RF transmission. Proceedings of the 2011 IEEE International Symposium on Medical Measurements and Applications, Bari, Italy. · doi:10.1109/memea.2011.5966704
  20. Kim, 2008, Microwave dielectric resonator biosensor for aqueous glucose solution, Rev. Sci. Instrum., 79, 086107, 10.1063/1.2968115 · doi:10.1063/1.2968115
  21. Yilmaz, T., Brizzi, A., Foster, R., Munoz, M., and Hao, Y. (2014, January 16–23). A patch resonator for sensing blood glucose changes. Proceedings of the 2014 XXXIth URSI General Assembly and Scientific Symposium (URSI GASS), Beijing, China. · doi:10.1109/ursigass.2014.6930125
  22. Kost, 2002, Ultrasound-Assisted Insulin Delivery and Noninvasive Glucose Sensing, Diabetes Technol. Ther., 4, 489, 10.1089/152091502760306571 · doi:10.1089/152091502760306571
  23. Siegel, P.H., Tang, A., Kim, R., Virbila, G., Chang, F., and Pikov, V. (September, January 27). Noninvasive in vivo millimeter-wave measurements of glucose: First results in human subjects. Proceedings of the 2017 42nd International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), Cancun, Mexico. · doi:10.1109/irmmw-thz.2017.8067035
  24. Zanon, M., Sparacino, G., Facchinetti, A., Talary, S.M., Mueller, M., Caduff, A., and Cobelli, C. (2013). Non-Invasive Continuous Glucose Monitoring with Multi-Sensor Systems: A Monte Carlo-Based Methodology for Assessing Calibration Robustness. Sensors, 13. · doi:10.3390/s130607279
  25. Tresp, 1999, Neural-network models for the blood glucose metabolism of a diabetic, IEEE Trans. Neural Netw., 10, 1204, 10.1109/72.788659 · doi:10.1109/72.788659
  26. Smith, J. (2018, December 14). Available online: https://www.researchgate.net/publication/317267760_The_Pursuit_of_Noninvasive_Glucose_5th_Edition.

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Metadata

Authors
Villena Gonzales, W., Mobashsher, A., & Abbosh, A.
Venue
Sensors
Publisher
MDPI AG
Published
2019-02-15
Volume
19
Issue
4
Pages
800
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s19040800
OpenAlex
W2914059200
Cited by
772
References
130
FWCI
60.06
Type
journal article
Language
en
Open access
gold
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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CoChat. (2026). Citation check: The Progress of Glucose Monitoring—A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors. https://app.cochat.ai/papers/10.3390/s19040800
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Villena Gonzales, W., Mobashsher, A., & Abbosh, A. (2019). The Progress of Glucose Monitoring—A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors. Sensors. https://doi.org/10.3390/s19040800

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