The DOI matches its Crossref record; 71 of the 73 references it cites were found in a registry or an index.
Current development in non-invasive glucose monitoring
Abstract
Painless control of blood glycemic levels could improve life quality of diabetes patients, enabling a better regulation of hyper- and hypoglycaemia episodes and thereby avoiding physiological complications. Although research groups have been trying for decades to separate non-invasive glucose information from interference compounds, none of the available commercial devices offers enough precision to replace lancet approaches. Many reviews have already been published on this topic, but the great amount of information available and the fast development of technologies require a continuous update in the research status. Besides the description of current in-vivo methods and the analysis of devices available commercially, one also explains treatment algorithms useful for multivariate analysis.
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“Almost all invasive sensing devices are characterized by infection risks, discomfort, and analytical response issues related to the foreign body response (FBR).29–30”
From Biocompatible Materials for Continuous Glucose Monitoring Devices (2013) · cites this paper as [29]
In the citing paper
“Additionally, sweating, often associated with hypoglycemia, affects the rate of extraction of glucose and therefore causes erroneous results when readings must be most accurate.29–30”
From Biocompatible Materials for Continuous Glucose Monitoring Devices (2013) · cites this paper as [29]
Citations
Cites
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(1997) · Series in medical physics and biomedical engineering · doi:10.1201/9781420050790 · Cited by 364
Performance Evaluation of the MiniMed® Continuous Glucose Monitoring System During Patient Home Use
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Koschinsky, T., & Heinemann, L. (2001) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.188 · Cited by 288
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2 of the 73 references couldn’t be matched to a known paper.
Cited by
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Recent advances in electrochemical glucose biosensors: a review
Chen, C., Xie, Q., Yang, D., Xiao, H., Fu, Y., Tan, Y., & Yao, S. (2012) · RSC Advances · doi:10.1039/c2ra22351a · Cited by 816
Glucose Sensing for Diabetes Monitoring: Recent Developments
Bruen, D., Delaney, C., Florea, L., & Diamond, D. (2017) · Sensors · doi:10.3390/s17081866 · Cited by 796
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
A contact lens with embedded sensor for monitoring tear glucose level
Yao, H., Shum, A. J., Cowan, M., Lähdesmäki, I., & Parviz, B. A. (2011) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2010.12.042 · Cited by 513
Liao, C., Mak, C., Zhang, M., Chan, H. L. W., & Yan, F. (2014) · Advanced Materials · doi:10.1002/adma.201404378 · Cited by 380
Metadata
- Authors
- Ferrante do Amaral, C. E., & Wolf, B.
- Affiliations
- Technical University of Munich (DE)
- Venue
- Medical Engineering & Physics
- Publisher
- IOP Publishing
- Published
- 2007-10-18
- Volume
- 30
- Issue
- 5
- Pages
- 541-549
- ISSN
- 1350-4533 (ISSN-L)
- 1873-4030
- OpenAlex
- W1975209404
- Cited by
- 269
- References
- 73
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 11 · 2023: 16 · 2022: 18 · 2021: 19 · 2020: 16 · 2019: 19 · 2018: 18 · 2017: 25 · 2016: 20 · 2015: 17 · 2014: 12 · 2013: 14 · 2012: 17
- FWCI
- 0.62
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Medical Engineering & Physics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Deutscher Akademischer Austauschdienst
- Heinz Nixdorf Stiftung
- U.S. Food and Drug Administration
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- non-invasive glucose monitoring, diabetes mellitus, glycemic control, hypoglycemia, hyperglycemia, multivariate analysis, treatment algorithm
- MeSH terms
- Blood Glucose, Humans, Monitoring, Physiologic, Physics, Spectrum Analysis, Physical Phenomena
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