The DOI matches its Crossref record; 149 of the 149 references it cites were found in a registry or an index.
Non-Invasive Blood Glucose Monitoring Technology: A Review
Open accessAbstract
In recent years, with the rise of global diabetes, a growing number of subjects are suffering from pain and infections caused by the invasive nature of mainstream commercial glucose meters. Non-invasive blood glucose monitoring technology has become an international research topic and a new method which could bring relief to a vast number of patients. This paper reviews the research progress and major challenges of non-invasive blood glucose detection technology in recent years, and divides it into three categories: optics, microwave and electrochemistry, based on the detection principle. The technology covers medical, materials, optics, electromagnetic wave, chemistry, biology, computational science and other related fields. The advantages and limitations of non-invasive and invasive technologies as well as electrochemistry and optics in non-invasives are compared horizontally in this paper. In addition, the current research achievements and limitations of non-invasive electrochemical glucose sensing systems in continuous monitoring, point-of-care and clinical settings are highlighted, so as to discuss the development tendency in future research. With the rapid development of wearable technology and transdermal biosensors, non-invasive blood glucose monitoring will become more efficient, affordable, robust, and more competitive on the market.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Indeed, it is remarkable that glucose levels in biofluids, such as ISF (Figure 4B), sweat (Figure 4C), saliva, tears, and urine (Figure 4 D, E, F, respectively) are correlated with those in the blood 76.”
From Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices (2022) · cites this paper as [76]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“As stated above, over the years, enzymatic amperometric glucose sensors were the first and widespread glucose sensors available 76.”
From Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices (2022) · cites this paper as [76]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“It is widely known that enzymatic sensors such as those based on glucose oxidase are more stable than other enzymes, easy to obtain, and cheap; on the other hand, it quickly loses its activity at pH<2 or pH>8 and can be irrevocably damaged at temperatures above 40 °C 76.”
From Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices (2022) · cites this paper as [76]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Standards of Medical Care in Diabetes
Power, D. V. (2006) · Diabetes Care · doi:10.2337/diacare.29.02.06.dc05-1593 · Cited by 8,676
Standards of medical care in diabetes—2014
American Diabetes Association (2014) · Diabetes Care · doi:10.2337/dc14-s014 · Cited by 4,572
Gabriel, S., Lau, R. W., & Gabriel, C. (1996) · Physics in Medicine and Biology · doi:10.1088/0031-9155/41/11/003 · Cited by 4,175
ELECTRODE SYSTEMS FOR CONTINUOUS MONITORING IN CARDIOVASCULAR SURGERY
Clark, L. C., & Lyons, C. (1962) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.1962.tb13623.x · Cited by 3,945
Electrochemical Glucose Biosensors
Wang, J. (2008) · Chemical Reviews · doi:10.1021/cr068123a · Cited by 3,498
Standards of medical care in diabetes 2010
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc10-s011 · Cited by 3,470
Nathan, D. M., & for the DCCT/EDIC Research Group (2014) · Diabetes Care · doi:10.2337/dc13-2112 · Cited by 1,832
Wearable and flexible electronics for continuous molecular monitoring
Yang, Y., & Gao, W. (2019) · Chemical Society Reviews · doi:10.1039/c7cs00730b · Cited by 1,315
Flexible Electronics toward Wearable Sensing
Gao, W. F., Ota, H., Kiriya, D., Takei, K., & Javey, A. (2019) · Accounts of Chemical Research · doi:10.1021/acs.accounts.8b00500 · Cited by 1,301
Microneedles: A smart approach and increasing potential for transdermal drug delivery system
Waghule, T., Singhvi, G., Dubey, S. K., Pandey, M. M., Gupta, G., Singh, M., & Dua, K. (2018) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2018.10.078 · Cited by 1,277
Flagged first, then by citations
Cited by
Sorted by citations
Flexible Wearable Sensors for Cardiovascular Health Monitoring
Chen, S., Qi, J., Fan, S., Qiao, Z., Yeo, J. C., & Lim, C. T. (2021) · Advanced Healthcare Materials · doi:10.1002/adhm.202100116 · Cited by 453
Pullano, S. A., Greco, M., Bianco, M. G., Foti, D., Brunetti, A., & Fiorillo, A. S. (2022) · Theranostics · doi:10.7150/thno.64035 · Cited by 210
“Indeed, it is remarkable that glucose levels in biofluids, such as ISF (Figure 4B), sweat (Figure 4C), saliva, tears, and urine (Figure 4 D, E, F, respectively) are correlated with those in the blood [76].”
BackgroundMethodInfluentialWu, Z., Qiao, Z., Chen, S., Fan, S., Liu, Y., Qi, J., & Lim, C. T. (2024) · Communications Materials · doi:10.1038/s43246-024-00468-6 · Cited by 204
Magnesium Oxide (MgO) Nanoparticles: Synthetic Strategies and Biomedical Applications
Gatou, Μ.-A., Skylla, E., Dourou, P., Pippa, Ν., Gazouli, M., Lаgopati, N., & Pavlatou, E. A. (2024) · Crystals · doi:10.3390/cryst14030215 · Cited by 176
Thwala, L. N., Ndlovu, S. C., Mpofu, K. T., Lugongolo, M. Y., & Mthunzi-Kufa, P. T. (2023) · Nanomaterials · doi:10.3390/nano13071247 · Cited by 171
Self-powered enzyme-linked microneedle patch for scar-prevention healing of diabetic wounds
Zhang, X., Wang, Z., Jiang, H. L., Zeng, H., An, N., Liu, B., Sun, L., & Fan, Z. (2023) · Science Advances · doi:10.1126/sciadv.adh1415 · Cited by 170
Mansour, M., Darweesh, M. S., & Soltan, A. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2024.01.021 · Cited by 165
Noninvasive Blood Glucose Monitoring Systems Using Near-Infrared Technology—A Review
Hina, A., & Saadeh, W. (2022) · Sensors · doi:10.3390/s22134855 · Cited by 156
Intelligent Wearable Systems: Opportunities and Challenges in Health and Sports
Yang, L., Amin, O., & Shihada, B. (2024) · ACM Computing Surveys · doi:10.1145/3648469 · Cited by 159
Techniques to Improve the Performance of Planar Microwave Sensors: A Review and Recent Developments
Abdolrazzaghi, M., Nayyeri, V., & Martı́n, F. (2022) · Sensors · doi:10.3390/s22186946 · Cited by 130
Dixit, K., Fardindoost, S., Ravishankara, A., Tasnim, N., & Hoorfar, M. (2021) · Biosensors · doi:10.3390/bios11120476 · Cited by 134
Jeon, H., Kim, H. S., Chung, E., & Lee, D. Y. (2022) · Theranostics · doi:10.7150/thno.72152 · Cited by 129
The LOD paradox: When lower isn't always better in biosensor research and development
Moulahoum, H., & Ghorbanizamani, F. (2024) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2024.116670 · Cited by 132
Type 1 diabetes glycemic management: Insulin therapy, glucose monitoring, and automation
Perkins, B. A., Sherr, J. L., & Mathieu, C. (2021) · Science · doi:10.1126/science.abg4502 · Cited by 116
Review of Microwave Near-Field Sensing and Imaging Devices in Medical Applications
Origlia, C., Rodriguez-Duarte, D. O., Vasquez, J. A. T., Bolomey, J., & Vipiana, F. (2024) · Sensors · doi:10.3390/s24144515 · Cited by 111
Zheng, L. L., Liu, Y., & Zhang, C. (2021) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2021.130131 · Cited by 103
Advancements in Wearable and Implantable BioMEMS Devices: Transforming Healthcare Through Technology
Abhinav, V., Basu, P., Verma, S. S., Verma, J., Das, A., Kumari, S., Yadav, P. R., & Kumar, V. (2025) · Micromachines · doi:10.3390/mi16050522 · Cited by 106
New advances in type 1 diabetes
Subramanian, S., Khan, F. N., & Hirsch, I. B. (2024) · BMJ · doi:10.1136/bmj-2023-075681 · Cited by 105
Non-invasive measurements of blood glucose levels by time-gating mid-infrared optoacoustic signals
Uluç, N., Glasl, S., Gasparin, F., Yuan, T., He, H., Jüstel, D., Pleitez, M. A., & Ntziachristos, V. (2024) · Nature Metabolism · doi:10.1038/s42255-024-01016-9 · Cited by 98
A Concise and Systematic Review on Non-Invasive Glucose Monitoring for Potential Diabetes Management
Laha, S., Rajput, A., Laha, S. S., & Jadhav, R. (2022) · Biosensors · doi:10.3390/bios12110965 · Cited by 91
Filippo, D. D., Sunstrum, F. N., Khan, J. U., & Welsh, A. W. (2023) · Sensors · doi:10.3390/s23229130 · Cited by 90
Applications of Microwaves in Medicine
Chiao, J. ‐., Li, C., Lin, J., Caverly, R. H., Hwang, J. C. M., Rosen, H. D., & Rosen, A. (2022) · IEEE Journal of Microwaves · doi:10.1109/jmw.2022.3223301 · Cited by 94
Commercial and Scientific Solutions for Blood Glucose Monitoring—A Review
Xue, Y., Thalmayer, A. S., Zeising, S., Fischer, G., & Lübke, M. (2022) · Sensors · doi:10.3390/s22020425 · Cited by 90
Microwave Planar Resonant Solutions for Glucose Concentration Sensing: A Systematic Review
Juan, C. G., Potelon, B., Quendo, C., & Bronchalo, E. (2021) · Applied Sciences · doi:10.3390/app11157018 · Cited by 84
Jarnda, K. V., Wang, D., Qurrat-Ul-Ain, Anaman, R., Johnson, V. E., Roberts, G. P., Johnson, P. S., Jallawide, B. W., Kai, T., & Ding, P. (2023) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2023.114778 · Cited by 83
Yin, S., Yu, Z., Song, N., Guo, Z., Li, W., Ma, J., Wang, X., Liu, J., & Liang, M. (2023) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2023.115822 · Cited by 83
Self-citationReview of Noninvasive Continuous Glucose Monitoring in Diabetics
Li, Y., & Chen, Y. (2023) · ACS Sensors · doi:10.1021/acssensors.3c01538 · Cited by 83
Technological Advances of Wearable Device for Continuous Monitoring of In Vivo Glucose
Huang, X., Yao, C., Huang, S., Zheng, S., Liu, Z., Liu, J., Wang, J., Chen, H., & Xie, X. (2024) · ACS Sensors · doi:10.1021/acssensors.3c01947 · Cited by 84
Self-citationPrendin, F., Favero, S. D., Vettoretti, M., Sparacino, G., & Facchinetti, A. (2021) · Sensors · doi:10.3390/s21051647 · Cited by 77
Liu, Y., Li, J., Xiao, S., Liu, Y., Bai, M., Gong, L., Zhao, J., & Chen, D. (2023) · Biosensors · doi:10.3390/bios13070726 · Cited by 77
Smart Contact Lenses—A Step towards Non-Invasive Continuous Eye Health Monitoring
Kazanskiy, N. L., Khonina, S. N., & Butt, M. A. (2023) · Biosensors · doi:10.3390/bios13100933 · Cited by 78
Shang, T., Zhang, J. Y., Thomas, A., Arnold, M. A., Vetter, B., Heinemann, L., & Klonoff, D. C. (2021) · Journal of Diabetes Science and Technology · doi:10.1177/19322968211007212 · Cited by 75
Continuous Glucose Monitoring in the Hospital
Perez‐Guzman, M. C., Shang, T., Zhang, J. Y., Jornsay, D. L., & Klonoff, D. C. (2021) · Endocrinology and Metabolism · doi:10.3803/enm.2021.201 · Cited by 72
Jarnda, K. V., Dai, H., Ali, A., Bestman, P. L., Trafiałek, J., Roberts-Jarnda, G. P., Anaman, R., Kamara, M. G., Wu, P., & Ding, P. (2025) · Biosensors · doi:10.3390/bios15040222 · Cited by 71
The Role of Nano-Sensors in Breath Analysis for Early and Non-Invasive Disease Diagnosis
Lаgopati, N., Valamvanos, T.-F., Proutsou, V., Karachalios, K., Pippa, Ν., Gatou, Μ.-A., Vagena, I.-A., Cela, S., Pavlatou, E. A., Gazouli, M., et al. (2023) · Chemosensors · doi:10.3390/chemosensors11060317 · Cited by 68
Zhao, J. C., Zhang, S., Sun, Y., Zhou, N., Yu, H., Zhang, H., & Jia, D. (2022) · ACS Photonics · doi:10.1021/acsphotonics.2c00898 · Cited by 63
An Overview of Wearable and Implantable Electrochemical Glucose Sensors
Zhu, B., Li, X., Zhou, L., & Su, B. (2021) · Electroanalysis · doi:10.1002/elan.202100273 · Cited by 63
A Self-Charging Supercapacitor for a Patch-Type Glucose Sensor
Kil, H.-J., Kim, S., & Park, J. (2022) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.1c21394 · Cited by 61
Susana, E., Ramli, K., Murfi, H., & Apriantoro, N. H. (2022) · Information · doi:10.3390/info13020059 · Cited by 59
Gut Microbiome Analysis for Personalized Nutrition: The State of Science
Simon, M., Sina, C., Ferrario, P. G., Daniel, H., & Working Group “Personalized Nutrition” of the German Nutrition Society (2022) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202200476 · Cited by 60
Glycated Hemoglobin and Methods for Its Point of Care Testing
Pohanka, M. (2021) · Biosensors · doi:10.3390/bios11030070 · Cited by 57
Venkatachalapathy, P., Padhilahouse, S., Sellappan, M., Subramanian, T., Kurian, S. J., Miraj, S. S., Rao, M., Raut, A. A., Kanwar, R. K., Singh, J., et al. (2021) · Pharmacogenomics and Personalized Medicine · doi:10.2147/pgpm.s329787 · Cited by 60
Subcutaneously implantable electromagnetic biosensor system for continuous glucose monitoring
Kim, S., Malik, J., Seo, J. M., Cho, Y. M., & Bien, F. D. (2022) · Scientific Reports · doi:10.1038/s41598-022-22128-w · Cited by 58
Engineered live bacteria as disease detection and diagnosis tools
Tanniche, I., & Behkam, B. (2023) · Journal of Biological Engineering · doi:10.1186/s13036-023-00379-z · Cited by 57
Noninvasive Diabetes Detection through Human Breath Using TinyML-Powered E-Nose
Gudiño-Ochoa, A., García-Rodríguez, J. A., Ochoa-Ornelas, R., Chávez, J. I. C., & Sánchez-Arias, D. A. (2024) · Sensors · doi:10.3390/s24041294 · Cited by 56
Nguenouho, O. S. B., Chevalier, A., Potelon, B., Bénédicto, J., & Quendo, C. (2022) · Scientific Reports · doi:10.1038/s41598-022-11355-w · Cited by 55
Fluorescence‐Amplified Origami Microneedle Device for Quantitatively Monitoring Blood Glucose
Li, X., Xu, X., Wang, K., Chen, Y., Zhang, Y., Si, Q., Pan, Z., Jia, F., Cui, X., Wang, X., et al. (2023) · Advanced Materials · doi:10.1002/adma.202208820 · Cited by 52
Non-invasive, ultrasensitive detection of glucose in saliva using metal oxide transistors
Sharma, A., AlGhamdi, W. S., Faber, H. A., Lin, Y., Liu, C., Hsu, E.-K., Lin, W., Naphade, D. R., Mandal, S. K., Heeney, M., et al. (2023) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2023.115448 · Cited by 51
Gilnezhad, J., Firoozbakhtian, A., Hosseini, M., Adel, S., Xu, G., & Ganjali, M. R. (2023) · Analytica Chimica Acta · doi:10.1016/j.aca.2023.340981 · Cited by 48
Comparative assessment of blood glucose monitoring techniques: a review
Ahmadian, N., Manickavasagan, A., & Ali, A. (2022) · Journal of Medical Engineering & Technology · doi:10.1080/03091902.2022.2100496 · Cited by 46
Recent Progress in Nanobiosensors for Precise Detection of Blood Glucose Level
Ardakani, H. K., Gerami, M., Chashmpoosh, M., Omidifar, N., & Gholami, A. (2022) · Biochemistry Research International · doi:10.1155/2022/2964705 · Cited by 46
The History, Evolution and Future of Continuous Glucose Monitoring (CGM)
Bender, C., Vestergaard, P., & Cichosz, S. L. (2025) · Diabetology · doi:10.3390/diabetology6030017 · Cited by 43
Recent Advances in Non-Enzymatic Glucose Sensors Based on Nanomaterials
Yang, D., Chen, Y., Che, S., & Wang, K. (2025) · Coatings · doi:10.3390/coatings15080892 · Cited by 43
Коноплев, Г., Agafonova, D. S., Bakhchova, L., Mukhin, N. V., Kurachkina, M., Schmidt, M.-P., Верлов, Н. А., Sidorov, A. I., Oseev, A., Stepanova, O. S., et al. (2022) · Biomedicines · doi:10.3390/biomedicines10020207 · Cited by 43
Susana, E., Ramli, K., Purnamasari, P. D., & Apriantoro, N. H. (2023) · Information · doi:10.3390/info14030145 · Cited by 45
Non-invasive blood glucose monitoring technology in diabetes management: review
Moses, J. C., Adibi, S., Wickramasinghe, N. S., Nguyen, L., Angelova, M. N., & Islam, S. M. S. (2024) · mHealth · doi:10.21037/mhealth-23-9 · Cited by 41
Wearable biosensors for human sweat glucose detection based on carbon black nanoparticles
Tang, C., Zhou, K., Wang, R., Li, M., Liu, W., Li, C., Chen, X., Lu, Q., & Chang, Y. (2024) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-024-05135-w · Cited by 42
Bavkar, V. C., & Shinde, A. A. (2021) · Indian Journal of Science and Technology · doi:10.17485/ijst/v14i10.2187 · Cited by 41
Smartphone-Based Electrochemical Systems for Glucose Monitoring in Biofluids: A Review
Xu, J., Yan, Z., & Liu, Q. (2022) · Sensors · doi:10.3390/s22155670 · Cited by 42
Eco-Friendly Conductive Hydrogels: Towards Green Wearable Electronics
Moreno, J. M. C., Chelu, M., & Popa, M. (2025) · Gels · doi:10.3390/gels11040220 · Cited by 41
Biosensors for healthcare: an artificial intelligence approach
Davé, S., Dave, A., Radhakrishnan, S., Das, J., & Dave, S. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-88464-8.00008-7 · Cited by 39
Electrochemical biosensors based on saliva electrolytes for rapid detection and diagnosis
Liu, J., Tang, Y., Cheng, Y., Huang, W., & Xiang, L. (2022) · Journal of Materials Chemistry B · doi:10.1039/d2tb02031a · Cited by 39
Self-citationKaysir, M. R., Song, J., Rassel, S., Aloraynan, A., & Ban, D. (2023) · Biosensors · doi:10.3390/bios13070716 · Cited by 38
Bimetallic Nanomaterials-Based Electrochemical Biosensor Platforms for Clinical Applications
Kannan, P., & Maduraiveeran, G. (2021) · Micromachines · doi:10.3390/mi13010076 · Cited by 38
Lakhera, P., Chaudhary, V., Bhardwaj, B., Kumar, P., & Kumar, S. (2022) · Biosensors and Bioelectronics X · doi:10.1016/j.biosx.2022.100218 · Cited by 37
Textile Antenna-Sensor for In Vitro Diagnostics of Diabetes
Gharbi, M. E., Fernández, R., & Gil, I. (2021) · Electronics · doi:10.3390/electronics10131570 · Cited by 36
Inobeme, A., Natarajan, A., Pradhan, S., Adetunji, C. O., Ajai, A. I., Inobeme, J., Tsado, M. J., Jacob, J. O., Pandey, S. S., Singh, K. R., et al. (2024) · Advanced Sensor Research · doi:10.1002/adsr.202400066 · Cited by 35
Mao, X., & Zhang, C. (2021) · Talanta · doi:10.1016/j.talanta.2021.123052 · Cited by 35
Todaro, B., Begarani, F., Sartori, F., & Luin, S. (2022) · Frontiers in Chemistry · doi:10.3389/fchem.2022.994272 · Cited by 37
Debele, T. A., & Park, Y. C. (2022) · Life · doi:10.3390/life12122078 · Cited by 34
Patent analysis of digital sensors for continuous glucose monitoring
Litvinova, O., Eitenberger, M., Bilir, A., Yeung, A. W. K., Parvanov, E. D., MohanaSundaram, A., Horbańczuk, J. O., Atanasov, A. G., & Willschke, H. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1205903 · Cited by 37
Lifestyle mediators of associations among siestas, obesity, and metabolic health
Vizmanos-Lamotte, B., Cascales, A. I., Rodríguez‐Martín, M., Salmerón, D., Morales, E., Alonso, A. A., Scheer, F. A. J. L., & Garaulet, M. (2023) · Obesity · doi:10.1002/oby.23765 · Cited by 34
Applications of flexible electronics related to cardiocerebral vascular system
Lin, R., Lei, M., Ding, S., Cheng, Q., Ma, Z., Wang, L., Tang, Z., Zhou, B., & Zhou, Y. (2023) · Materials Today Bio · doi:10.1016/j.mtbio.2023.100787 · Cited by 34
Kansay, V., Sharma, V. D., Srivastava, V., Batra, N., Chakrabarti, S., & Bera, M. K. (2024) · Microchemical Journal · doi:10.1016/j.microc.2024.110624 · Cited by 33
Review—Energy and Power Requirements for Wearable Sensors
Arya, S. K., Sharma, A., Singh, A., Ahmed, A., Dubey, A., Padha, B., Khan, S., Mahadeva, R., Khosla, A., & Gupta, V. (2024) · ECS Sensors Plus · doi:10.1149/2754-2726/ad54d2 · Cited by 34
Ma, R., Shao, R., An, X., Zhang, Q., & Sun, S. (2022) · Journal of Materials Chemistry B · doi:10.1039/d2tb00749e · Cited by 34
Caldara, M., Kulpa, J., Lowdon, J. W., Cleij, T. J., Diliën, H., Eersels, K., & van Grinsven, B. (2023) · Chemosensors · doi:10.3390/chemosensors11010032 · Cited by 33
Non-invasive glucose prediction and classification using NIR technology with machine learning
Naresh, M. S., Nagaraju, V. S., Kollem, S., Kumar, J., & Peddakrishna, S. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e28720 · Cited by 40
Advancements in nanobiosensor technologies for in-vitro diagnostics to point of care testing
Kim, C., Kang, M. S., Raja, I. S., Joung, Y. K., & Han, D. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e40306 · Cited by 32
Breath Analysis for the In Vivo Detection of Diabetic Ketoacidosis
Sha, M. S., Maurya, M. R., Shafath, S., Cabibihan, J., Al-Ali, A. K., Malik, R. A., & Sadasivuni, K. K. (2022) · ACS Omega · doi:10.1021/acsomega.1c05948 · Cited by 35
Giaretta, J., Zulli, R., Prabhakar, T., Rath, R. J., Naficy, S., Spilimbergo, S., Weiss, P. S., Farajikhah, S., & Dehghani, F. (2024) · Advanced Sensor Research · doi:10.1002/adsr.202400065 · Cited by 31
Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems
Kaushal, A., Musafir, A., Sharma, G., Rani, S., Singh, R. K., Kumar, A., Bhadada, S. K., Barnwal, R. P., & Singh, G. (2025) · Pharmaceutics · doi:10.3390/pharmaceutics17060777 · Cited by 31
Nelis, J. L. D., Bose, U., Broadbent, J. A., Hughes, J. M., Sikes, A. L., Anderson, A. R., Caron, K., Schmoelzl, S., & Colgrave, M. L. (2022) · Comprehensive Reviews in Food Science and Food Safety · doi:10.1111/1541-4337.12935 · Cited by 31
Hamed, M. M., Mohammed, N. A., & Badawi, K. A. (2025) · Scientific Reports · doi:10.1038/s41598-025-87547-x · Cited by 30
Shang, L.-J., Yu, S.-Q., Shang, X.-W., Wei, X., Wang, H., Jiang, W., & Ren, Q. (2024) · Journal of Applied Electrochemistry · doi:10.1007/s10800-023-02065-w · Cited by 29
Kuppuswamy, G. P., Matada, M. S. S., Marappan, G., Mulla, M. Y., Jayaraman, S. V., Natale, C. D., & Sivalingam, Y. (2023) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.3c00339 · Cited by 29
Morulane, K. L., Tshabalala, Z. P., Swart, H. C., & Motaung, D. E. (2024) · Applied Surface Science · doi:10.1016/j.apsusc.2024.160714 · Cited by 28
Song, S., Wang, Q., Zou, X., Li, Z., Ma, Z., Jiang, D., Fu, Y., & Liu, Q. (2023) · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy · doi:10.1016/j.saa.2023.123176 · Cited by 28
Feasibility Evaluation of Metamaterial Microwave Sensors for Non-Invasive Blood Glucose Monitoring
Malena, L., Fišer, O., Stauffer, P. R., Drizdal, T., Vrba, J., & Vrba, D. (2021) · Sensors · doi:10.3390/s21206871 · Cited by 27
Mustafa, A., Alsafari, I. A., Somaily, H. H., Yousaf, S., Din, M. I., Rahman, J., Shahid, M., Ashraf, M., & Warsi, M. F. (2022) · Physica B Condensed Matter · doi:10.1016/j.physb.2022.414404 · Cited by 26
Ringholm, L., Nørgaard, S. K., Rytter, A., Damm, P., & Mathiesen, E. R. (2022) · Nutrients · doi:10.3390/nu14224867 · Cited by 26
Gaidukevič, J., Aukštakojytė, R., Kozłowski, M., Barkauskas, J., & Pauliukaitė, R. (2023) · Electrochimica Acta · doi:10.1016/j.electacta.2023.142113 · Cited by 26
Hybrid CNN-LSTM for Predicting Diabetes: A Review
Soltanizadeh, S., & Naghibi, S. S. (2023) · Current Diabetes Reviews · doi:10.2174/0115733998261151230925062430 · Cited by 25
Ortiz‐Martínez, M., Flores-DelaToba, R., González‐González, M., & Rito‐Palomares, M. (2021) · Biosensors · doi:10.3390/bios11120482 · Cited by 25
Zhang, M., Zhang, S., Wang, Q., Xu, Y., Jiang, L., Yan, Y., Li, J., Tian, Z., & Zhang, W. (2023) · Advanced Materials Technologies · doi:10.1002/admt.202300775 · Cited by 25
Kil, H.-J., Kim, J. H., Lee, K., Kang, T.-U., Yoo, J.-H., Lee, Y., & Park, J. (2024) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2024.116297 · Cited by 26
Global Overview of Environmental Enrichment Studies: What Has Been Done and Future Directions
Bachetti, E. D. S., Viol, L. Y., Junior, A. B. V., Young, R. J., & de Azevedo, C. S. (2024) · Animals · doi:10.3390/ani14111613 · Cited by 24
Bockholt, R., Paschke, S., Heubner, L., Ibarlucea, B., Laupp, A., Janićijević, Ž., Klinghammer, S., Balakin, S., Maitz, M. F., Werner, C., et al. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11092408 · Cited by 26
Patra, S., Purohit, S. S., & Swain, S. K. (2023) · Microchemical Journal · doi:10.1016/j.microc.2023.108646 · Cited by 24
What makes a medical intervention invasive?
Marco, G. D., Simons, J., Forsberg, L., & Douglas, T. (2023) · Journal of Medical Ethics · doi:10.1136/jme-2023-109301 · Cited by 25
Metadata
- Authors
- Tang, L., Chang, S. J., Chen, C.-J., & Liu, J.-T.
- Affiliations
- Research Center for Materials Science and Opti-Electronic Technology, College of Materials Science and Opti-Electronic Technology, University of Chinese Academy of Sciences, Beijing 100049, China
- I-Shou University (TW)
- University of Chinese Academy of Sciences (CN)
- Corresponding author
- Chen, Ching-Jung
- Liu, Jen-Tsai
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2020-12-04
- Volume
- 20
- Issue
- 23
- Pages
- 6925
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC7731259
- OpenAlex
- W3106856419
- Cited by
- 481
- References
- 149
- Citations by year
- 2026: 66 · 2025: 100 · 2024: 101 · 2023: 111 · 2022: 71 · 2021: 32
- FWCI
- 2.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Chinese Academy of Sciences
- University of Chinese Academy of Sciences
- Topics
- Physical Sciences › Chemistry › Analytical Chemistry › Electrochemical sensors and biosensors
- 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, optical glucose sensing, electrochemical glucose sensor, continuous glucose monitoring, point-of-care testing, wearable sensors
- MeSH terms
- Wearable Electronic Devices, Blood Glucose, Humans, Monitoring, Physiologic, Blood Glucose Self-Monitoring, Biosensing Techniques
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