Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future Directions

Diabetes mellitus has emerged as a major chronic disease threatening global health. While traditional glucometers enable point-of- care testing, their invasive nature induces patient resistance that significantly compromises disease management efficacy. Contemporary non-invasive technologies have ac...

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Main Author: Wu Kerui
Format: Article
Language:English
Published: EDP Sciences 2025-01-01
Series:MATEC Web of Conferences
Online Access:https://www.matec-conferences.org/articles/matecconf/pdf/2025/04/matecconf_menec2025_04002.pdf
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author Wu Kerui
author_facet Wu Kerui
author_sort Wu Kerui
collection DOAJ
description Diabetes mellitus has emerged as a major chronic disease threatening global health. While traditional glucometers enable point-of- care testing, their invasive nature induces patient resistance that significantly compromises disease management efficacy. Contemporary non-invasive technologies have achieved breakthrough progress, yet critical research gaps persist in multi-physics coupling mechanisms and personalized calibration model development. This comprehensive review analyzes principle innovations and industrial applications of non-invasive glucose monitoring technologies, employing technical evolution pathway analysis and clinical data benchmarking to evaluate seven methodological paradigms - including spectroscopy, electrochemistry, and microwave sensing - along with their translational achievements in wearable devices and healthcare systems. Key findings demonstrate: multi-modal sensing reduces detection errors to 8.7% through signal complementarity, with millimeter-wave radar technology achieving 5-minute continuous monitoring (r=0.912); flexible electronic skin breakthroughs 72-hour operational endurance (sensitivity 0.03nA/(mg/dL)); and intelligent closed-loop systems enhance glycated hemoglobin compliance rates by 42%. Current technical bottlenecks manifest as individual calibration variation coefficients exceeding 12% and blood-interstitial fluid glucose lag (8-15 minutes), with emerging solutions trending toward deep learning-based dynamic compensation models (83% error correction) and terahertz quantum cascade detection (0.1mmol/L detection limit).
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spelling doaj-art-058b631e109c48d59525ea008a5249442025-08-20T03:58:36ZengEDP SciencesMATEC Web of Conferences2261-236X2025-01-014100400210.1051/matecconf/202541004002matecconf_menec2025_04002Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future DirectionsWu Kerui0Reading College, Nanjing University of Information Science and Technology (NUIST)Diabetes mellitus has emerged as a major chronic disease threatening global health. While traditional glucometers enable point-of- care testing, their invasive nature induces patient resistance that significantly compromises disease management efficacy. Contemporary non-invasive technologies have achieved breakthrough progress, yet critical research gaps persist in multi-physics coupling mechanisms and personalized calibration model development. This comprehensive review analyzes principle innovations and industrial applications of non-invasive glucose monitoring technologies, employing technical evolution pathway analysis and clinical data benchmarking to evaluate seven methodological paradigms - including spectroscopy, electrochemistry, and microwave sensing - along with their translational achievements in wearable devices and healthcare systems. Key findings demonstrate: multi-modal sensing reduces detection errors to 8.7% through signal complementarity, with millimeter-wave radar technology achieving 5-minute continuous monitoring (r=0.912); flexible electronic skin breakthroughs 72-hour operational endurance (sensitivity 0.03nA/(mg/dL)); and intelligent closed-loop systems enhance glycated hemoglobin compliance rates by 42%. Current technical bottlenecks manifest as individual calibration variation coefficients exceeding 12% and blood-interstitial fluid glucose lag (8-15 minutes), with emerging solutions trending toward deep learning-based dynamic compensation models (83% error correction) and terahertz quantum cascade detection (0.1mmol/L detection limit).https://www.matec-conferences.org/articles/matecconf/pdf/2025/04/matecconf_menec2025_04002.pdf
spellingShingle Wu Kerui
Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future Directions
MATEC Web of Conferences
title Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future Directions
title_full Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future Directions
title_fullStr Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future Directions
title_full_unstemmed Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future Directions
title_short Non-Invasive Glucose Monitoring Technologies Innovations Applications and Future Directions
title_sort non invasive glucose monitoring technologies innovations applications and future directions
url https://www.matec-conferences.org/articles/matecconf/pdf/2025/04/matecconf_menec2025_04002.pdf
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