Systems and methods to noninvasively enhance the visual acuity for patients with retinal prostheses

Unmet Need

Degenerative eye diseases lead to a profound decrease in quality of life, and their incidence is on the rise. In high- and middle-income countries, age-related macular degeneration is the main and growing cause of blindness, with about 11 million people affected in the U.S. alone that is projected to increase to 22 million by 2050. Retinal prostheses restore some visual perception for those with degenerative eye diseases by sending externally captured video to an electrode array implanted in the eye, replacing the function of the retina. The global market for these bionic eyes is projected to grow rapidly, from $10.6 million in 2019 to an estimated $35.7 million in 2024, a CAGR of 27.5%. This is a potentially transformative treatment, yet the resolution of bionic eyes is currently limited by the constrictive size requirements for the implanted electrode array – even the most advanced retinal prostheses provide roughly 1/10th the resolution considered sufficient to perform day-to-day tasks. There is a need for improving the image resolution for people using retinal prostheses.


A Duke inventor is developing systems and methods for improving the image resolution for people using retinal prostheses. This approach takes advantage of the brain's inherent ability, called super resolution, to fuse together a series of moving low resolution images to achieve greater visual clarity. Dr. Sina Farsiu is reversing this process: algorithmically deconstructing a higher resolution video from an external camera into sequences of lower resolution frames that can be delivered to a retinal prosthesis in near real time. The brain's natural super resolution capabilities then take over and improve visual acuity. The basics of this system are being built and the effect of image movement on visual acuity due to super resolution are being investigated in laboratory experiments.

Other Applications

Can be used as a component of a diagnostic test for visual acuity and as a research tool to further explore how image movement affects visual acuity.


  • Improves image resolution for patients with existing retinal prostheses without the need for new implants
  • Delivers images that are perceived at a higher resolution than a retinal prosthesis electrode array allows
  • Can be applied to retinal prostheses in development to additionally improve image resolution
  • Reduces the need for patients needing to manually scan with head motion, like when their retinal prostheses have damaged electrodes
  • Can be integrated with other functionality, for example for improving large object edge detection