Trial reportJournal of diabetes science and technology2010
Noninvasive glucose monitoring: increasing accuracy by combination of multi-technology and multi-sensors.
Trial report in Journal of diabetes science and technology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Investigation of glucose-induced thermo-optical and polarizability effects in blood plasma for optical biomolecular differentiation.Physical and engineering sciences in medicine · 2026Article
- 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
- Biosensor-Integrated Drug Delivery Systems as New Materials for Biomedical Applications.Biomolecules · 2022Review
- Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities.Biosensors · 2021Review
- Noninvasive Glucose Monitoring: In God We Trust-All Others Bring Data.Journal of diabetes science and technology · 2021Article
- 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
- Review of Non-invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone.Sensors (Basel, Switzerland) · 2020Review
- Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device.Sensors (Basel, Switzerland) · 2019Article
- The Progress of Glucose Monitoring-A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors.Sensors (Basel, Switzerland) · 2019Review
- First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View.Journal of diabetes science and technology · 2018Article
- In vivo Microscopic Photoacoustic Spectroscopy for Non-Invasive Glucose Monitoring Invulnerable to Skin Secretion Products.Scientific reports · 2018Article
- Disruption in the diabetic device care market.Medical devices (Auckland, N.Z.) · 2018Review
- The accuracy of a non-invasive glucose monitoring device does not depend on clinical characteristics of people with type 2 diabetes mellitus.Journal of drug assessment · 2018Article
- Noninvasive Continuous Glucose Monitoring Using a Multisensor-Based Glucometer and Time Series Analysis.Scientific reports · 2017Article
- Assessing the Performance of a Noninvasive Glucose Monitor in People with Type 2 Diabetes with Different Demographic Profiles.Journal of diabetes research · 2017Article
- Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review.Sensors (Basel, Switzerland) · 2016Review
- The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System.Journal of diabetes science and technology · 2015Article
- Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.Journal of diabetes science and technology · 2014Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe main concern in noninvasive (NI) glucose monitoring methods is to achieve high accuracy results despite the fact that no direct blood or interstitial fluid glucose measurement is performed. An alternative approach to increase the accuracy of NI glucose measurement was previously suggested through a combination of three NI methods: ultrasonic, electromagnetic, and thermal. This paper provides further explanation about the nature of the implemented technologies, and multi-sensors are presented, as well as a detailed elaboration on the novel algorithm for data analysis.
methodsClinical trials were performed on two different days. During the first day, calibration and six subsequent measurements were performed. During the second day, a "full day" session of about 10 hours took place. During the trial, type 1 and 2 diabetes patients were calibrated and evaluated with GlucoTrack glucose monitor against HemoCue (Glucose 201+).
resultsA total of 91 subjects were tested during the trial period. Clarke error grid (CEG) analysis shows 96% of the readings (on both days 1 and 2) fall in the clinically accepted A and B zones, of which 60% are within zone A. The absolute relative differences (ARDs) yield mean and median values of 22.4% and 15.9%, respectively. The CEG for day 2 of the trial shows 96% of the points in zones A and B, with 57% of the values in zone A. Mean and median ARD values for the readings on day 2 are 23.4% and 16.5%, respectively. The intervals between day 1 (calibration and measurements) and day 2 (measurements only) were 1-22 days, with a median of 6 days.
conclusionsThe presented methodology shows that increased accuracy was indeed achieved by combining multi-technology and multi-sensors. The approach of integration contributes to increasing the signal-to-noise ratio (glucose to other contributors). A combination of several technologies allows compensation of a possible aberration in one modality by the others, while multi-sensor implementation enables corrections for interference contributions. Furthermore, clinical trials indicate the ability of using the device for a wide range of demography, showing clearly that the calibration is valid for long term.
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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 OpenQuestion graph.