Researchers at BITS Pilani, Hyderabad, have unveiled an innovative Machine Learning (ML)-assisted non-invasive portable device for diabetes detection and management. This groundbreaking solution eliminates the need for finger-pricking by using sweat or urine to monitor critical biomarkers such as glucose, lactate, uric acid, and hydrogen peroxide.
The device employs Electro-Chemi-Luminescence (ECL) technology, which uses light emitted during specific electrochemical reactions to detect biomarkers with high precision and minimal background noise. It integrates seamlessly with smartphones via an app, enabling real-time, continuous monitoring for better glycemic control.
Priced at just ₹700–₹800 per unit, with polymeric cartridges costing only ₹10 per test in bulk production, this cost-effective innovation promises to make diabetes management more accessible.
Principal investigator Sanket Goel, from the MEMS, Microfluidics, and Nanoelectronics Lab, emphasized its significance: “We expect the device to become a frontrunner in providing accessible and efficient diagnostics in real-time. It offers immense potential for commercialization and widespread adoption in healthcare systems worldwide.”
Developed by a team led by Dr. Sanket Goel, including PhD scholar Abhishek Kumar and intern Shashwat Goel, the device has received support from the Telangana State Council of Science & Technology and the Council of Scientific and Industrial Research. The findings have been published in the esteemed Computers in Biology and Medicine journal by Elsevier.
With its affordability, ease of use, and advanced biosensing technology, this device is set to transform diabetes care, making it invaluable for healthcare professionals managing Type 1 and Type 2 diabetes.
