ArticleJournal of diabetes science and technology2018
Device and Method for Noninvasive Glucose Assessment.
Article in Journal of diabetes science and technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Evaluation of a New Noninvasive Glucose Monitoring Device by Means of Standardized Meal Experiments.Journal of diabetes science and technology · 2018Trial
- Advancing Diabetic Care Through Non-Invasive Glucose Monitoring Using Optical Sensors and IoT Technologies.F1000Research · 2026Article
- A Feasibility Study on Noninvasive Blood Glucose Estimation Using Machine Learning Analysis of Near-Infrared Spectroscopy Data.Biosensors · 2025Article
- AI-Based Noninvasive Blood Glucose Monitoring: Scoping Review.Journal of medical Internet research · 2024Article
- Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.Diabetes care · 2023Review
- Noninvasive Glucose Sensing In Vivo.Sensors (Basel, Switzerland) · 2023Review
- Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.Clinical chemistry · 2023Article
- Improving the Accuracy of Continuous Blood Glucose Measurement Using Personalized Calibration and Machine Learning.Diagnostics (Basel, Switzerland) · 2023Article
- Patent analysis of digital sensors for continuous glucose monitoring.Frontiers in public health · 2023Review
- Is Raman the best strategy towards the development of non-invasive continuous glucose monitoring devices for diabetes management?Frontiers in chemistry · 2022Review
- Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities.Biosensors · 2021Review
- A Review of Non-Invasive Optical Systems for Continuous Blood Glucose Monitoring.Sensors (Basel, Switzerland) · 2021Review
- Low-cost portable microwave sensor for non-invasive monitoring of blood glucose level: novel design utilizing a four-cell CSRR hexagonal configuration.Scientific reports · 2020Article
- Adaptive Boosting Based Personalized Glucose Monitoring System (PGMS) for Non-Invasive Blood Glucose Prediction with Improved Accuracy.Diagnostics (Basel, Switzerland) · 2020Article
- System Accuracy Assessment of a Combined Invasive and Noninvasive Glucometer.Journal of diabetes science and technology · 2020Article
- Review of Non-invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone.Sensors (Basel, Switzerland) · 2020Review
- New Paradigm of Personalized Glycemic Control Using Glucose Temporal Density Histograms.Journal of diabetes science and technology · 2019Article
- The Progress of Glucose Monitoring-A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors.Sensors (Basel, Switzerland) · 2019Review
- Noninvasive Monitoring of Blood Glucose Using Color-Coded Photoplethysmographic Images of the Illuminated Fingertip Within the Visible and Near-Infrared Range: Opportunities and Questions.Journal of diabetes science and technology · 2018Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntensive monitoring of blood glucose levels is crucial in diabetes management. This article presents a new device, the TensorTip Combo Glucometer (CoG), developed by Cnoga Medical Ltd, which enables to predict capillary tissue glucose concentration noninvasively.
methodsNoninvasive glucose readings usually provide irregular or disordered mathematical manifold over the measurement space. To establish a transfer function, which correctly correlates the noninvasive raw data and the actual invasive glucose level, we suggest a mathematical concept that employs a personal calibration procedure to associate glucose pattern and multiple optical signals derived from tissue response to light emission in the range of visible to IR. The traversed light is detected by a color image sensor to predict the tissue glucose concentration at the fingertip. This article presents the mathematical concept underlying the technology and the requirements for device operation.
resultsThe device was clinically evaluated and compared to standard invasive blood glucose monitoring devices in few medical centers and by home users. Based on consensus error grid analysis, more than 98% of the measurements of each study were in zones A (more than 81%) and B (more than 11%). Postmarketing evaluations showed high correlations comparing the CoG to other invasive reference devices.
conclusionsThe CoG device employs a unique mathematical approach to predict glucose concentrations based on multiple optical signals. The first clinical results indicate that the device may show appropriate agreement with reference methods to be used for pain-free glucose assessment in daily routine.
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