Retinal Degenerative Diseases (RDD) are among the major causes of adult-age blindness and low-vision worldwide. Unfortunately, to-date it is not possible to reverse the retinal damage, however, efforts are in progress to slow down the retinal degeneration process and provide rehabilitation to the RDD individuals through certain devices and training programs. The focus of these rehabilitation devices and training programs is to utilize the residual vision and develop a significant Preferred Retinal Locus/loci (PRL). Perceptual Learning (PL) training is shown to bring a positive change in a patient’s life quality, but this training is generalized and does not address an individual’s scotoma and saccade patterns. Can we use Artificial Intelligence (AI) to develop customized PL training for each individual.

This project offers a robust, adaptive, and intelligent PL training solution that integrates classical rehabilitation techniques with modern AI technology for clinical applications to improve quality of life for RDD affected patients. Our aim is to use eye-tracking to learn saccade patterns based on an individual’s PRL. Based on these saccade patterns, customized two-dimensional PL exercises will be designed using which subjects can learn to develop strategies to enhance spatial representation skills and develop significant PRL/PRLs. We also aim to use this training data of saccades in 2-D for three-dimensional PL inside a room or by using virtual reality, to develop better strategies for eye movements using PRL in real world. The use of AI-based PL training can help RDD individuals to rapidly develop an effective PRL that can help them significantly in better understanding of environment and improvement in quality of life.

Primary Goals

To develop a smart rehabilitation solution for Retinal Degenerative Diseases (RDD) based on patient’s own visual field specifications (saccades and blind-spots) so that they can learn faster utilizing their residual vision.

Infrastructure Needed: Access to Tobii Eyetracker at NUST, Islamabad, Pakistan.
Experimental space/room at hospital.

Principal Investigator

Co-Principal Investigators

Syed Omer Gilani (Academic Co-PI)

Google Scholar 

Industrial Collaborator(s)

N-ovative Health Technologies (NHT) Pvt Ltd,

Dr. Murtaza Najabat Ali


Co-Funding Provided (if any):  PKR: Nil

Scientific Field(s)

Low-vision rehabilitation, Artificial Intelligence


12 months


7 Million PKR
situs togel situs togel situs togel situs toto slot gacor slot gacor situs toto