Next-Generation Diabetes Care: Robust Adaptive Optimal Glucose Control Using Machine Learning, Wearable Integration and Microwave Sensors

Managing diabetes effectively is vital to prevent complications such as heart disease, nerve damage, and kidney issues. This research shows that weight control and tailored interventions can improve blood sugar and metabolic health. This paper reviews the microwave sensor for continuous, real-time glucose monitoring, designed for wearables like smartwatches. By integrating type-2 fuzzy-logic and machine learning, the sensors can offer accurate glucose readings and monitor additional physiological markers, optimizing personalized interventions for type-1 diabetes. This innovation will aim to advance diabetes management with reliable, user-friendly health monitoring.

• Publication year

  2024

• Venue

  2024 4th International Conference on Robotics, Automation and Artificial Intelligence (RAAI)

• Publication date

  2024-12-19

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/RAAI64504.2024.10949556
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• On-body non-invasive glucose monitoring sensor based on high figure of merit (FoM) surface plasmonic microwave resonator

  2023cited by this paper
• A novel method for diabetes classification and prediction with Pycaret

  2023cited by this paper
• Noninvasive Continuous Glucose Monitoring With a Novel Wearable Dial Resonating Sensor: A Clinical Proof-of-Concept Study

  2023cited by this paper
• A Miniature and Reusable Radiofrequency Biosensor Combining Microfluidic and Integrated Passive Technology for Glucose Detection

  2023influential reference
• Generalized Type-2 Fuzzy Control for Type-I Diabetes: Analytical Robust System

  2022cited by this paper
• An automated all-in-one system for carbohydrate tracking, glucose monitoring, and insulin delivery.

  2022cited by this paper
• Robust dynamic output feedback control of blood glucose level in diabetic rat with robust descriptor Kalman filter

  2022cited by this paper
• Robust Polytopic-LPV Body-Weight-Dependent Control of Blood Glucose in Type-1 Diabetes

  2021cited by this paper
• Wearable Glucose Monitoring and Implantable Drug Delivery Systems for Diabetes Management

  2021influential reference
• Sensing of Life Activities at the Human-Microwave Frontier

  2021cited by this paper
• Predictive modelling and analytics for diabetes using a machine learning approach

  2020cited by this paper
• Passive and wireless, implantable glucose sensing with phenylboronic acid hydrogel-interlayer RF resonators.

  2020influential reference
• Artificial Intelligence in Health Care: Predictive Analysis on Diabetes Using Machine Learning Algorithms

  2020cited by this paper
• Microwave Noninvasive Blood Glucose Monitoring Sensor: Penetration Depth and Sensitivity Analysis

  2018cited by this paper
• Pain-Free Blood Glucose Monitoring Using Wearable Sensors: Recent Advancements and Future Prospects

  2018cited by this paper
• Microwave noninvasive blood glucose monitoring sensor: Human clinical trial results

  2017cited by this paper
• Wearable Continuous Glucose Monitoring Sensors: A Revolution in Diabetes Treatment

  2017cited by this paper
• Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association

  2016cited by this paper
• Recommendations for Using Real-Time Continuous Glucose Monitoring (rtCGM) Data for Insulin Adjustments in Type 1 Diabetes

  2016cited by this paper
• Brief report: Comparison of continuous glucose monitoring and finger-prick blood glucose levels in hospitalized patients administered basal-bolus insulin.

  2013cited by this paper
• Standards of Medical Care in Diabetes—2009

  2009cited by this paper
• A microwave frequency sensor for non-invasive blood-glucose measurement

  2008cited by this paper
• Wireless body sensor networks for health-monitoring applications

  2008cited by this paper

• No citing papers are available for this paper.