ArticleScientific reports2022
Wearable flexible body matched electromagnetic sensors for personalized non-invasive glucose monitoring.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Stage-Wise IoT Solutions for Alzheimer's Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies.Sensors (Basel, Switzerland) · 2025Pooled it
- Non-Invasive Technologies in Wearable Glucose Monitoring: A Structured Overview for the Future.Biosensors · 2026Review
- Sensitivity Evaluation of a Dual-Finger Metamaterial Biosensor for Non-Invasive Glycemia Tracking on Multiple Substrates.Sensors (Basel, Switzerland) · 2025Article
- Flexible and Wearable Tactile Sensors for Intelligent Interfaces.Materials (Basel, Switzerland) · 2025Review
- Non-contact measurement of glucose in urine by smartphone-based laser refractometry for diabetes monitoring.Scientific reports · 2025Article
- Blood Glucose Monitoring Biosensor Based on Multiband Split-Ring Resonator Monopole Antenna.Biosensors · 2025Article
- Clinical evaluation of a polarization-based optical noninvasive glucose sensing system.Scientific reports · 2025Article
- Trends and Advances in Wearable Plasmonic Sensors Utilizing Surface-Enhanced Raman Spectroscopy (SERS): A Comprehensive Review.Sensors (Basel, Switzerland) · 2025Review
- Article
- Revolutionizing Diabetes Care: From Tech to Therapeutics.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- A comprehensive review on electromagnetic wave based non-invasive glucose monitoring in microwave frequencies.Heliyon · 2024Review
- Leveraging Machine Learning for Personalized Wearable Biomedical Devices: A Review.Journal of personalized medicine · 2024Review
- 3D Printing of Dietary Products for the Management of Inborn Errors of Intermediary Metabolism in Pediatric Populations.Nutrients · 2023Review
- Non-Invasive Glucose Sensing Technologies and Products: A Comprehensive Review for Researchers and Clinicians.Sensors (Basel, Switzerland) · 2023Review
- Revolutionizing Precision Medicine: Exploring Wearable Sensors for Therapeutic Drug Monitoring and Personalized Therapy.Biosensors · 2023Review
- A new generation of sensors for non-invasive blood glucose monitoring.American journal of translational research · 2023Review
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This work introduces novel body-matched, vasculature-inspired, quasi-antenna-arrays that act as electromagnetic sensors to instantaneously, continuously, and wirelessly sense glucose variations in the bloodstream. The proposed sensors are personalized, leverage electromagnetic waves, and are coupled with a custom machine-learning-based signal-processing module. These sensors are flexible, and embedded in wearable garments such as socks, which provide conformity to curved skin surfaces and movement resilience. The entire wearable system is calibrated against temperature, humidity, and movement resulting in high accuracy in glucose variations tracking. In-Vivo experiments on diabetic rats and pigs exhibit a 100% diagnostic accuracy over a wide range of glucose variations. Human trials on patients with diabetes and healthy individuals reveal a clinical accuracy of continuous glucose monitoring of 99.01% in twenty-eight subjects who underwent Oral Glucose Tolerance Tests. Hence, our approach ensures the continuous tracking of glucose variations from hypo-to-hyper glycemic levels with great fidelity.
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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.