The DOI matches its Crossref record; 70 of the 70 references it cites were found in a registry or an index.
Non-invasive glucose monitoring: Assessment of technologies and devices according to quantitative criteria
Abstract
Aim of this review was to describe the main technologies for non-invasive glucose monitoring and the corresponding most relevant devices. The review tries to overcome the limitations of previous reviews on this topic, such as the lack of objective criteria for inclusion or exclusion of technologies or devices, and the poor organization of the information, which often does not allow easy comparison between technologies and devices. In this review, the information is concise and organized into specific categories, and hence it becomes easy to compare advantages and disadvantages of the different technologies and devices. For technologies, the categories of information considered are the technology name, the underlying physical principle, the technology limitations and the measurement sites on the human body. For devices, the categories of information are the device name, its approval condition (FDA Approval and/or CE Mark), the technology on which it is based, a device general description, the tests performed on the device, the corresponding results, safety information, aspects affecting usability, current status of the device and the manufacturer, an Internet reference for the device. A total of 14 technologies and 16 devices are included. Conclusions of the review were that, despite some interesting and promising technologies and devices, a satisfactory solution to the non-invasive glucose monitoring problem still requires further efforts.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Optical detection of glucose via near infrared (NIR) spectroscopy enables 90–95% of the light to pass through the human stratum corneum and epidermis into subcutaneous space with minimal tissue adsorption independent of skin pigmentation.19,40–41”
From Biocompatible Materials for Continuous Glucose Monitoring Devices (2013) · cites this paper as [41]
Citations
Cites
Evaluating clinical accuracy of systems for self-monitoring of blood glucose
Clarke, W. L., Cox, D., Gonder-Frederick, L. A., Carter, W., & Pohl, S. L. (1987) · Diabetes Care · doi:10.2337/diacare.10.5.622 · Cited by 1,435
Prospects forin vivoRaman spectroscopy
Hanlon, E. B., Manoharan, R., Koo, T.-W., Shafer‐Peltier, K., Motz, J. T., Fitzmaurice, M., Kramer, J. R., Itzkan, I., Dasari, R. R., & Feld, M. S. (2000) · Physics in Medicine and Biology · doi:10.1088/0031-9155/45/2/201 · Cited by 906
Diabetes Control and Complications Trial
Yue, D. K., Colagiuri, S., McElduff, A., & Silink, M. (1993) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.1993.tb141357.x · Cited by 575
Hyponatremia: evaluating the correction factor for hyperglycemia
Hillier, T. A., Abbott, R. D., & Barrett, E. J. (1999) · The American Journal of Medicine · doi:10.1016/s0002-9343(99)00055-8 · Cited by 567
Monnier, V. M., Bautista, O., Kenny, D., Sell, D. R., Fogarty, J., Dahms, W., Cleary, P. A., Lachin, J., & Genuth, S. (1999) · Diabetes · doi:10.2337/diabetes.48.4.870 · Cited by 469
Combined In Vivo Confocal Raman Spectroscopy and Confocal Microscopy of Human Skin
Caspers, P. J., Lucassen, G. W., & Puppels, G. J. (2003) · Biophysical Journal · doi:10.1016/s0006-3495(03)74501-9 · Cited by 453
Tierney, M. J., Tamada, J. A., Potts, R. O., Jovanovic, L., & Garg, S. (2001) · Biosensors and Bioelectronics · doi:10.1016/s0956-5663(01)00189-0 · Cited by 390
Yonzon, C. R., Haynes, C. L., Zhang, X., Walsh, & Van Duyne, R. P. (2004) · Analytical Chemistry · doi:10.1021/ac035134k · Cited by 376
Spectroscopic and Clinical Aspects of Noninvasive Glucose Measurements
Khalil, O. S. (1999) · Clinical Chemistry · doi:10.1093/clinchem/45.2.165 · Cited by 331
Noninvasive Blood Glucose Monitoring With Optical Coherence Tomography
Larin, K. V., Eledrisi, M. S., Motamedi, M., & Esenaliev, R. O. (2002) · Diabetes Care · doi:10.2337/diacare.25.12.2263 · Cited by 300
Research works printed but not linked: 2
- R.W. Waynant, V.M. Chenault, Overview of non-invasive fluid glucose measurement using optical techniques to maintain glucose control in diabetes mellitus (http://www.ieee.org/organizations/pubs/newsletters/leos/apr98/overview.htm. Last checked 22/03/2006).
- R.J. McNichols, B.D. Cameron, G.L. Coté, Development of a non-invasive polarimetric glucose sensor (http://www.ieee.org/organizations/pubs/newsletters/leos/apr98/glucosesensor.htm. Last checked 22/03/2006).
Cited by
Sorted by citations
Sacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Kirkman, M. S., Lernmark, A., Metzger, B. E., & Nathan, D. M. (2011) · Clinical Chemistry · doi:10.1373/clinchem.2010.161596 · Cited by 1,360
Gonzales, W. V., Mobashsher, A. T., & Abbosh, A. M. (2019) · Sensors · doi:10.3390/s19040800 · Cited by 820
Sacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Kirkman, M. S., Lernmark, A., Metzger, B. E., & Nathan, D. M. (2011) · Diabetes Care · doi:10.2337/dc11-9998 · Cited by 718
Non-invasive glucose monitoring technology in diabetes management: A review
Vashist, S. K. (2012) · Analytica Chimica Acta · doi:10.1016/j.aca.2012.03.043 · Cited by 575
Skin-like biosensor system via electrochemical channels for noninvasive blood glucose monitoring
Chen, Y., Lu, S., Zhang, S., Li, Y., Qu, Z., Chen, Y., Lu, B., Wang, X., & Feng, X. (2017) · Science Advances · doi:10.1126/sciadv.1701629 · Cited by 470
Metadata
- Authors
- Tura, A., Maran, A., & Pacini, G.
- Affiliations
- National Research Council (IT)
- University of Padua (IT)
- Corresponding author
- Tura, Andrea
- Venue
- Diabetes Research and Clinical Practice
- Publisher
- Elsevier BV
- Published
- 2007-07
- Volume
- 77
- Issue
- 1
- Pages
- 16-40
- ISSN
- 0168-8227 (ISSN-L)
- OpenAlex
- W2139729200
- Cited by
- 283
- References
- 70
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 11 · 2023: 11 · 2022: 12 · 2021: 14 · 2020: 19 · 2019: 16 · 2018: 21 · 2017: 24 · 2016: 16 · 2015: 22 · 2014: 26 · 2013: 17 · 2012: 22
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes Research and Clinical Practice (publishedVersion)
- PubMed (publishedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Keywords
- non-invasive glucose monitoring, blood glucose measurement, diabetes mellitus, glucose monitoring devices, FDA approval, CE marking, device safety, usability, measurement site
- MeSH terms
- Adult, Blood Glucose, Child, Endocrinology, Humans, Iontophoresis, Patient Compliance, Spectrum Analysis, Spectrum Analysis, Raman, Ultrasonics, Blood Glucose Self-Monitoring, Electric Impedance, Device Approval, Spectroscopy, Near-Infrared
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review