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Cited by 291

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Current and Emerging Technology for Continuous Glucose Monitoring

Open access
Chen, Cheng, Zhao, Xue-Ling, Li, Zhan-Hong, Zhu, Zhi-Gang, Qian, Shao-Hong, Flewitt, Andrew·2017·Sensors

Abstract

Diabetes has become a leading cause of death worldwide. Although there is no cure for diabetes, blood glucose monitoring combined with appropriate medication can enhance treatment efficiency, alleviate the symptoms, as well as diminish the complications. For point-of-care purposes, continuous glucose monitoring (CGM) devices are considered to be the best candidates for diabetes therapy. This review focuses on current growth areas of CGM technologies, specifically focusing on subcutaneous implantable electrochemical glucose sensors. The superiority of CGM systems is introduced firstly, and then the strategies for fabrication of minimally-invasive and non-invasive CGM biosensors are discussed, respectively. Finally, we briefly outline the current status and future perspective for CGM systems.

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Registry

Crossref · 10.3390/s17010182

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Metadata

Authors
Chen, C., Zhao, X.-L., Li, Z.-H., Zhu, Z.-G., Qian, S.-H., & Flewitt, A.
Venue
Sensors
Publisher
MDPI AG
Published
2017-01-19
Volume
17
Issue
1
Pages
182
ISSN
1424-8220 (ISSN-L)
OpenAlex
W2577350032
Cited by
291
References
13
FWCI
12.31
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Current and Emerging Technology for Continuous Glucose Monitoring. https://app.cochat.ai/papers/10.3390/s17010182
The paper
Chen, C., Zhao, X.-L., Li, Z.-H., Zhu, Z.-G., Qian, S.-H., & Flewitt, A. (2017). Current and Emerging Technology for Continuous Glucose Monitoring. Sensors. https://doi.org/10.3390/s17010182

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.