System for screening and early detection of diabetic retinopathy

Main results to June 30, 2021

A basal non-evoked electroretinogram (ERG) revealed that animals and humans present intrinsic oscillations, whose characteristics change when the patient has pre-diabetes, metabolic syndrome, or diabetes with or without diabetic retinopathy. This information is relevant to proposing a system that automatically analyzes and classifies these oscillations based on their characteristics for screening tests, early detection, and follow-up of diabetic retinopathy.

The system relies on ERG recordings acquired under basal conditions, i.e. in the absence of an explicit light stimulus. It is worth noting that the code runs after making the recording, and the basal ERG is an electrical signal recorded noninvasively from the front of the eye or the skin near the eye without a light stimulus.

The system uses records from patients receiving or not receiving therapy; it automatically analyzes and classifies the intrinsic oscillatory electrical signals measured by non-evoked ERG to predict the percentage risk of having retinal dysfunction associated or not with diabetes. It is a web app that the user can easily access from any web browser.