ArticleACS sensors2023
Accurate Post-Calibration Predictions for Noninvasive Glucose Measurements in People Using Confocal Raman Spectroscopy.
Article in ACS sensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 43 citations in OpenAlex.
- A Flexible Wearable Glucose Sensor for Noninvasive Diabetes Screening: Functional Equivalence and Model Interpretability.Biosensors · 2026Article
- From Drops to Decisions: AI/ML-Driven Biofluidics for Clinical Diagnostics and Healthcare Intelligence.Analytical chemistry · 2026Review
- Clinical validation of noninvasive blood glucose measurements by midinfrared spectroscopy.Communications medicine · 2025Article
- Calibration and performance of a Raman-based device for non-invasive glucose monitoring in type 2 diabetes.Scientific reports · 2025Article
- Clinical evaluation of a polarization-based optical noninvasive glucose sensing system.Scientific reports · 2025Article
- Subcutaneous depth-selective spectral imaging with mμSORS enables noninvasive glucose monitoring.Nature metabolism · 2025Article
- Flexible Non-Enzymatic Glucose Sensors: One-Step Green Synthesis of NiO Nanoporous Films via an Electro-Exploding Wire Technique.ACS applied materials & interfaces · 2024Article
- Highly Sensitive Perovskite Photoplethysmography Sensor for Blood Glucose Sensing Using Machine Learning Techniques.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Accuracy enhancement of metabolic index-based blood glucose estimation with a screening process for low-quality data.Journal of biomedical optics · 2024Article
- Diabetes Technology Meeting 2023.Journal of diabetes science and technology · 2024Article
- Engineering vascularized skin-mimetic phantom for non-invasive Raman spectroscopy.Sensors and actuators. B, Chemical · 2024Article
- Non-invasive blood glucose estimation method based on the phase delay between oxy- and deoxyhemoglobin using visible and near-infrared spectroscopy.Journal of biomedical optics · 2024Article
- A Novel Biosensor for the Detection of Glucose Concentration Using the Dual-Peak Long Period Grating in the Near- to Mid-Infrared.Sensors (Basel, Switzerland) · 2024Article
- Blood glucose monitoring devices for type 1 diabetes: a journey from the food and drug administration approval to market availability.Frontiers in endocrinology · 2024Review
- Electrospun Manganese-Based Metal-Organic Frameworks for MnOACS omega · 2023Article
- Label-Free Human Disease Characterization through Circulating Cell-Free DNA Analysis Using Raman Spectroscopy.International journal of molecular sciences · 2023Article
Corrections and comments
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Authors and funding
13 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In diabetes prevention and care, invasiveness of glucose measurement impedes efficient therapy and hampers the identification of people at risk. Lack of calibration stability in non-invasive technology has confined the field to short-term proof of principle. Addressing this challenge, we demonstrate the first practical use of a Raman-based and portable non-invasive glucose monitoring device used for at least 15 days following calibration. In a home-based clinical study involving 160 subjects with diabetes, the largest of its kind to our knowledge, we find that the measurement accuracy is insensitive to age, sex, and skin color. A subset of subjects with type 2 diabetes highlights promising real-life results with 99.8% of measurements within A + B zones in the consensus error grid and a mean absolute relative difference of 14.3%. By overcoming the problem of calibration stability, we remove the lingering uncertainty about the practical use of non-invasive glucose monitoring, boding a new, non-invasive era in diabetes monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.