GIST Develops Diabetes Self-Diagnosis System Using Contact Lenses

Diabetes Diagnosis Through Glucose Concentration in Tears
Analysis Using Color Change of Nanoparticles with Camera

[Asia Economy Honam Reporting Headquarters Reporter Cho Hyung-joo] The research team led by Professor Jeong Ui-heon of the Department of Biomedical Engineering at GIST (Gwangju Institute of Science and Technology), in collaboration with Professor Lee Dong-yoon of the Department of Biotechnology at Hanyang University (Ilix PharmaTech), announced on the 30th that they have developed a smart contact lens that is harmless to the human body and does not require electrodes.

The conventional diagnosis of diabetes is typically an invasive method that measures glucose concentration in blood collected by pricking the fingertip with a needle.

Pricking the finger with a needle every time to measure blood sugar causes significant psychological stress to patients and also carries the risk of side effects such as infection through the needle.

The research team confirmed the possibility of diagnosing diabetes by using tears, one of the major body fluids highly correlated with disease states, instead of blood, and proceeded with the development of a smart contact lens that measures glucose concentration in tears.

For 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 concentration in tears and can measure blood sugar levels by linking with a smartphone.

The research team developed a system in which nanoparticles in the lens exhibit color changes according to the glucose concentration in tears, and a precise imaging system to capture the degree of color change, as well as an eye-tracking algorithm that minimizes measurement errors caused by eye movement. The eye-tracking algorithm is designed to enable more precise measurements and allow self-diagnosis of diabetes.

Additionally, the smart contact lens developed in this study does not require electrodes and minimizes the burden on the body by quantitatively analyzing the color change of biocompatible nanoparticles through a camera.

Professor Jeong Ui-heon of GIST explained, “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.”

Professor Lee Dong-yoon of Hanyang University stated, “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 less burden on patients compared to existing diagnostic methods.”

This research was led by Professor Jeong Ui-heon (corresponding author) of GIST and Professor Lee Dong-yoon (corresponding author) of Hanyang University, and conducted by Dr. Jeon Hee-jae, supported by the Korea Research Foundation’s Biomedical Technology Development Project and others. The related paper was published online on August 20, 2021, in the prestigious international journal in the field of nanotechnology, Nano Letters. It is also scheduled to be published as a supplementary cover article in the print edition.

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