Development of Smart Lens Diagnosing Diabetes Through Tears

Professor Jeong Euiheon and GIST Research Team, "Measuring Glucose Concentration in Tears to Diagnose Diabetes"

[Asia Economy Reporter Kim Bong-su] A groundbreaking technology has been developed that measures blood sugar using tears, enabling diabetes management. This will significantly reduce the burden on patients who have to prick their fingers to draw blood.

Gwangju Institute of Science and Technology (GIST) announced on the 30th that a joint research team led by Professor Jeong Ui-heon of the Department of Biomedical Engineering and Professor Lee Dong-yoon of Hanyang University's Department of Biotechnology has developed a smart contact lens that can measure glucose concentration in tears without electrodes and is harmless to the human body.

Previously, diagnosing and managing diabetes required pricking the fingertip with a needle to collect blood and measure glucose levels. Repeated finger pricking caused significant psychological stress for patients. There was also a risk of side effects such as infection through the needle.

The research team developed the smart contact lens by confirming the possibility of diagnosing diabetes through glucose concentration in tears, one of the major body fluids correlated with disease states, instead of blood. This is because in diabetic patients, when blood glucose levels rise, glucose levels in other body fluids also increase.

The contact lens developed by the research team changes color according to the glucose level in tears and can measure blood sugar levels in connection with a smartphone. Nanoparticles inside the lens change color based on the glucose concentration in tears, and a system capable of precisely capturing the degree of color change was developed, along with an eye-tracking algorithm that minimizes measurement errors caused by eye movement. The eye-tracking algorithm was designed to enable more precise measurement and self-diagnosis of diabetes. By quantitatively analyzing the color change of harmless nanoparticles through a camera without requiring electrodes, the physical burden on the body is minimized.

Professor Jeong said, "This achievement is a technology that can reduce the biggest drawback of existing diabetes diagnostic methods, which is invasive measurement. In the future, if deep learning technology and bio big data are utilized, it could become a more precise non-invasive method in daily life." He added, "If safety evaluations through clinical trials are conducted in the future, it is expected that diabetes self-diagnosis will be possible more conveniently and with minimal burden on patients compared to existing diagnostic methods."

The research results were published online on the 20th in the international journal in the field of nanotechnology, Nano Letters. It is also scheduled to be published as a supplementary cover paper in the print edition.

This content was produced with the assistance of AI translation services.