Back close

Non-invasive Detection of Glucose using Planar RF Sensors

Dept/Center/Lab: Amrita Center for Wireless Networks and Applications (AWNA)

Non-invasive Detection of Glucose using Planar RF Sensors

Non-invasive glucose detection using planar RF (radio frequency) prototypes is a promising approach that leverages RF technology to monitor blood glucose levels without the need for blood samples. This method involves using RF signals to detect glucose concentration changes in the interstitial fluid under the skin.  Glucose levels influence the dielectric properties of body tissues, such as permittivity and conductivity. By measuring these changes, RF sensors can estimate glucose concentration.

Name of Staff and Students from Amrita : Ms Meenu L, Ms Bhuvana Nair S

Publication Details

  1. Aiswarya, S., Meenu, L., Menon, S. K., & Menon, K. U. (2022, December). Analysis and Validation of Planar Microwave Diagonal Stub Loaded Closed Loop Resonator for Glucose Monitoring. In 2022 URSI Regional Conference on Radio Science (USRI-RCRS) (pp. 1-4). IEEE.
  2. Aiswarya, S., S. Bhuvana Nair, L. Meenu, and Sreedevi K. Menon. “Analysis and design of stub loaded closed loop microstrip line filter for Wi-Fi applications.” In 2019 Sixteenth International Conference on Wireless and Optical Communication Networks (WOCN), pp. 1-5. IEEE, 2019.

Related Projects

Analysis of Throat Film Cooling for Semi Cryogenic Thrust Chamber
Analysis of Throat Film Cooling for Semi Cryogenic Thrust Chamber
High Temperature Thermoplastic Hybrid Composite for Higher Tensile Strength and Impact Resistance
High Temperature Thermoplastic Hybrid Composite for Higher Tensile Strength and Impact Resistance
Medical Signal Processing using IoT Devices
Medical Signal Processing using IoT Devices
Inhibitory Effect of Plant Extracts on Siderophore Production in Klebsiella Pneumoniae
Inhibitory Effect of Plant Extracts on Siderophore Production in Klebsiella Pneumoniae
Hardware Trojan Detection & Consistency based Diagnosis
Hardware Trojan Detection & Consistency based Diagnosis
Admissions Apply Now