ArticleScientific reports2017
Noninvasive Continuous Glucose Monitoring Using a Multisensor-Based Glucometer and Time Series Analysis.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Noninvasive Interstitial Glucose Estimation Using Wearables and Machine Learning in Healthy Individuals and Individuals With Obesity: Observational Cohort Study.JMIR mHealth and uHealth · 2026Observational
- Design of a microwave sensor for non-invasive monitoring of blood glucose level with high sensitivity using electromagnetic properties.Scientific reports · 2026Article
- Digital biomarkers for interstitial glucose prediction in healthy individuals using wearables and machine learning.Scientific reports · 2025Article
- Noninvasive Continuous Glucose Monitoring Using Multimodal Near-Infrared, Temperature, and Pressure Signals on the Earlobe.Biosensors · 2025Article
- Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management.Sensors (Basel, Switzerland) · 2024Article
- Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.Diabetes care · 2023Review
- Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.Clinical chemistry · 2023Article
- Evaluation of a Continuous Blood Glucose Monitor: A Novel and Non-Invasive Wearable Using Bioimpedance Technology.Journal of diabetes science and technology · 2023Observational
- Comparisons of artificial intelligence algorithms in automatic segmentation for fungal keratitis diagnosis by anterior segment images.Frontiers in neuroscience · 2023Article
- Noninvasive Blood Glucose Monitoring Systems Using Near-Infrared Technology-A Review.Sensors (Basel, Switzerland) · 2022Review
- Commercial and Scientific Solutions for Blood Glucose Monitoring-A Review.Sensors (Basel, Switzerland) · 2022Review
- Analytical Model for Blood Glucose Detection Using Electrical Impedance Spectroscopy.Sensors (Basel, Switzerland) · 2020Article
- Theoretical Simulation of the Near-Field Probe for Non-Invasive Measurements on Planar Layers with Biological Characteristics.Bioengineering (Basel, Switzerland) · 2020Article
- Reusable, Non-Invasive, and Ultrafast Radio Frequency Biosensor Based on Optimized Integrated Passive Device Fabrication Process for Quantitative Detection of Glucose Levels.Sensors (Basel, Switzerland) · 2020Article
- Review of Non-invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone.Sensors (Basel, Switzerland) · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Daily continuous glucose monitoring is very helpful in the control of glucose levels for people with diabetes and impaired glucose tolerance. In this study, a multisensor-based, noninvasive continuous glucometer was developed, which can continuously estimate glucose levels via monitoring of physiological parameter changes such as impedance spectroscopy at low and high frequency, optical properties, temperature and humidity. Thirty-three experiments were conducted for six healthy volunteers and three volunteers with diabetes. Results showed that the average correlation coefficient between the estimated glucose profiles and reference glucose profiles reached 0.8314, with a normalized root mean squared error (NRMSE) of 14.6064. The peak time of postprandial glucose was extracted from the glucose profile, and its estimated value had a correlation coefficient of 0.9449 with the reference value, wherein the root mean square error (RMSE) was 6.8958 min. Using Clarke error grid (CEG) analysis, 100% of the estimated glucose values fell in the clinically acceptable zones A and B, and 92.86% fell in zone A. The application of a multisensor-based, noninvasive continuous glucometer and time series analysis can endure the time delay between human physiological parameters and glucose level changes, so as to potentially accomplish noninvasive daily continuous glucose monitoring.
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