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Cited by 491Electrochemical sensors and biosensorsSpectroscopy Techniques in Biomedical and Chemical ResearchNon-Invasive Vital Sign Monitoring

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 access
Tang, Liu, Chang, Shwu Jen, Chen, Ching-Jung, Liu, Jen-Tsai·2020·Sensors
DOI 10.3390/s20236925PMC PMC7731259
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Abstract

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.

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Crossref · 10.3390/s20236925

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Figures

Figure 1 Contrast of glucose concentrations in different physiological fluids between healthy and diabetic people.
Figure 1 Contrast of glucose concentrations in different physiological fluids between healthy and diabetic people.CC BY · PubMed Central
Figure 2 Schematic diagram of the second-generation glucose biosensor.
Figure 2 Schematic diagram of the second-generation glucose biosensor.CC BY · PubMed Central
Figure 3 Near-infrared (NIR) and mid-infrared (MIR) spectroscopy methods. (A) Noninvasive and fast measurement of blood glucose in vivo by NIR spectroscopy. Adapted with permission [46]. Copyright 2017, Elsevier. (B) Rapid and non-destructive measurement of glucose in a skin tissue phantom by near-infrared spectroscopy. Adapted with permission [47]. Copyright 2018, Elsevier. (C) Mid-infrared photoacoustic detection of glucose in human skin: towards non-invasive diagnostics. Adapted with permission [35]. Copyright 2016, MDPI. (D) Vibrational sensing using infrared nanoantennas: toward the non-invasive quantitation of physiological levels of glucose and fructose. Adapted with permission [48]. Copyright 2019, American Chemical Society.
Figure 3 Near-infrared (NIR) and mid-infrared (MIR) spectroscopy methods. (A) Noninvasive and fast measurement of blood glucose in vivo by NIR spectroscopy. Adapted with permission [46]. Copyright 2017, Elsevier. (B) Rapid and non-destructive measurement of glucose in a skin tissue phantom by near-infrared spectroscopy. Adapted with permission [47]. Copyright 2018, Elsevier. (C) Mid-infrared photoacoustic detection of glucose in human skin: towards non-invasive diagnostics. Adapted with permission [35]. Copyright 2016, MDPI. (D) Vibrational sensing using infrared nanoantennas: toward the non-invasive quantitation of physiological levels of glucose and fructose. Adapted with permission [48]. Copyright 2019, American Chemical Society.CC BY · PubMed Central
Figure 4 Optical polarimetry method: dual-wavelength polarimetric glucose sensing. Adapted with permission [67]. Copyright 2013, SPIE.
Figure 4 Optical polarimetry method: dual-wavelength polarimetric glucose sensing. Adapted with permission [67]. Copyright 2013, SPIE.CC BY · PubMed Central
Figure 5 Raman spectroscopy methods. (A) multicomponent analysis using a confocal Raman microscope. Adapted with permission [68]. Copyright 2018, Optical Society of America. (B) Glucose sensing using surface-enhanced Raman-mode constraining. Adapted with permission [69]. Copyright 2018, American Chemical Society.
Figure 5 Raman spectroscopy methods. (A) multicomponent analysis using a confocal Raman microscope. Adapted with permission [68]. Copyright 2018, Optical Society of America. (B) Glucose sensing using surface-enhanced Raman-mode constraining. Adapted with permission [69]. Copyright 2018, American Chemical Society.CC BY · PubMed Central
Figure 6 Fluorescence methods. (A) Colorimetric and ratiometric fluorescence dual-mode sensing of glucose. Adapted with permission [75]. Copyright 2019, MDPI. (B) Carbon-dot-based ratiometric fluorescence glucose biosensor. Adapted with permission [73]. Copyright 2019, Elsevier. (C) Nanostructured biosensor for detecting glucose in tear by applying fluorescence resonance energy transfer quenching mechanism. Adapted with permission [76]. Copyright 2017, Elsevier. Optical coherence tomography (OCT) method: (D) Non-invasive monitoring of blood glucose concentration in diabetic patients with optical coherence tomography. Adapted with permission [77]. Copyright 2017, Laser Physics Letters.
Figure 6 Fluorescence methods. (A) Colorimetric and ratiometric fluorescence dual-mode sensing of glucose. Adapted with permission [75]. Copyright 2019, MDPI. (B) Carbon-dot-based ratiometric fluorescence glucose biosensor. Adapted with permission [73]. Copyright 2019, Elsevier. (C) Nanostructured biosensor for detecting glucose in tear by applying fluorescence resonance energy transfer quenching mechanism. Adapted with permission [76]. Copyright 2017, Elsevier. Optical coherence tomography (OCT) method: (D) Non-invasive monitoring of blood glucose concentration in diabetic patients with optical coherence tomography. Adapted with permission [77]. Copyright 2017, Laser Physics Letters.CC BY · PubMed Central
Figure 7 Microwave methods. (A) High-sensitivity, quantified, linear and mediator-free resonator-based microwave biosensor for glucose detection. (a) Microwave-based glucose biosensor, (b) micro-fabricated biochip mounted printed circuit board (PCB), and (c) sensing mechanism of microwave biosensor. Adapted with permission [91]. Copyright 2020, MDPI. (B) Demonstration of microstrip sensor for the feasibility study of non-invasive blood-glucose sensing. Adapted with permission [92]. Copyright 2020, Springer.
Figure 7 Microwave methods. (A) High-sensitivity, quantified, linear and mediator-free resonator-based microwave biosensor for glucose detection. (a) Microwave-based glucose biosensor, (b) micro-fabricated biochip mounted printed circuit board (PCB), and (c) sensing mechanism of microwave biosensor. Adapted with permission [91]. Copyright 2020, MDPI. (B) Demonstration of microstrip sensor for the feasibility study of non-invasive blood-glucose sensing. Adapted with permission [92]. Copyright 2020, Springer.CC BY · PubMed Central
Figure 8 Schematic diagram of reverse iontophoresis (RI).
Figure 8 Schematic diagram of reverse iontophoresis (RI).CC BY · PubMed Central
Figure 9 Saliva-based and breath acetone glucose monitoring. (A) Non-invasive glucose monitoring using saliva nano-biosensor. Adapted with permission [108]. Copyright 2015, Elsevier. (B) Non-invasive measurement of blood glucose by breath analysis. Adapted with permission [129]. Copyright 2020, John Wiley and Sons.
Figure 9 Saliva-based and breath acetone glucose monitoring. (A) Non-invasive glucose monitoring using saliva nano-biosensor. Adapted with permission [108]. Copyright 2015, Elsevier. (B) Non-invasive measurement of blood glucose by breath analysis. Adapted with permission [129]. Copyright 2020, John Wiley and Sons.CC BY · PubMed Central
Figure 10 Tear-based glucose monitoring. (A) Paper-based colorimetric biosensor for tear glucose measurements. Adapted with permission [131]. Copyright 2017, Micromachines. (B) Tear glucose detection combining microfluidic thread based device, amperometric biosensor and microflow injection analysis. Adapted with permission [109]. Copyright 2017, Elsevier. (C) Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays. Adapted with permission [137]. Copyright 2018, Science advances.
Figure 10 Tear-based glucose monitoring. (A) Paper-based colorimetric biosensor for tear glucose measurements. Adapted with permission [131]. Copyright 2017, Micromachines. (B) Tear glucose detection combining microfluidic thread based device, amperometric biosensor and microflow injection analysis. Adapted with permission [109]. Copyright 2017, Elsevier. (C) Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays. Adapted with permission [137]. Copyright 2018, Science advances.CC BY · PubMed Central
Figure 11 Sweat-based glucose monitoring. (A) Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module. Adapted with permission [138]. Copyright 2017, Science advances. (B) Enokitake mushroom-like standing gold nanowires toward wearable noninvasive bimodal glucose and strain sensing. Adapted with permission [110]. Copyright 2019, American Chemical Society.
Figure 11 Sweat-based glucose monitoring. (A) Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module. Adapted with permission [138]. Copyright 2017, Science advances. (B) Enokitake mushroom-like standing gold nanowires toward wearable noninvasive bimodal glucose and strain sensing. Adapted with permission [110]. Copyright 2019, American Chemical Society.CC BY · PubMed Central
Figure 12 ISF-based glucose monitoring. (A) Skin-like biosensor system via electrochemical channels for noninvasive blood glucose monitoring. Adapted with permission [111]. Copyright 2017, Science advances. (B) Non-invasive, transdermal, path-selective and specific glucose monitoring via a graphene-based platform. Adapted with permission [142]. Copyright 2018, Nature Nanotechnology.
Figure 12 ISF-based glucose monitoring. (A) Skin-like biosensor system via electrochemical channels for noninvasive blood glucose monitoring. Adapted with permission [111]. Copyright 2017, Science advances. (B) Non-invasive, transdermal, path-selective and specific glucose monitoring via a graphene-based platform. Adapted with permission [142]. Copyright 2018, Nature Nanotechnology.CC BY · PubMed Central
Figure 13 Gelatin methacryloyl microneedle patches for minimally invasive extraction of skin interstitial fluid. (A) Preparation process of the GelMA MN patch. (B) Schematic diagram of the extraction process in a rat model. (C) The detected glucose concentration (blue dots) was fitted as a line (blue line), R2 = 0.981. (D) A picture of the GelMA MN patch containing an 11 × 11 array of MNs over a 1 cm × 1 cm area. (E) Detected glucose concentrations in ISF compared to blood glucose concentrations. * p < 0.05, NS means not significant. Adapted with permission [147]. Copyright 2020, Small.
Figure 13 Gelatin methacryloyl microneedle patches for minimally invasive extraction of skin interstitial fluid. (A) Preparation process of the GelMA MN patch. (B) Schematic diagram of the extraction process in a rat model. (C) The detected glucose concentration (blue dots) was fitted as a line (blue line), R2 = 0.981. (D) A picture of the GelMA MN patch containing an 11 × 11 array of MNs over a 1 cm × 1 cm area. (E) Detected glucose concentrations in ISF compared to blood glucose concentrations. * p < 0.05, NS means not significant. Adapted with permission [147]. Copyright 2020, Small.CC BY · PubMed Central

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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
ORCID
Venue
Sensors
Publisher
MDPI AG
Published
2020-12-04
Volume
20
Issue
23
Pages
6925
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s20236925
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
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

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