Automated Low Vision Rehabilitation System Using Real - Time Gaze Analysis (ARIANA)

The challenge

Age-related macular degeneration (AMD) is a global leading cause of vision loss in the elderly, and patients with AMD may develop central scotoma, which causes them to experience vision-related Activity of Daily Living (ADL) difficulties.

People with AMD experience irreversible central vision loss and they must rely on their functional peripheral vision for daily visual tasks. Low vision rehabilitation is an important step towards individuals with AMD regaining useful functional vision and quality of life.

The mainstay treatment for low vision rehabilitation of AMD patients relies on magnification or aims to train patients to use Eccentric Viewing (EV) by identifying and using the Preferred Retinal Locus (PRL) consistently for daily visual tasks.

EV training effectively improves the vision-related tasks of AMD patients with a central scotoma. In addition, the training of visual function to maximise a patient’s residual vision is essential for the efficient use of low vision aids. However, given the high reliance on manual efforts in the current process of rehabilitation and subjectivity, there remains a strong need to develop more efficient and effective programmes.

The proposed solution

ARIANA is an automated rehabilitative system that:

• uses real-time gaze analysis to objectively identify an individual’s PRL for useful functional vision and provides Eccentric Viewing Training in an automated way.
• provides automated assessments to monitor patient progress in functional vision rehabilitation.

The system can potentially lead to cost and time savings, increased vision rehabilitation efficiencies and home-based vision rehabilitation.