Improving face perception and quality of life in age-related macular degeneration

Abstract

The ability to see faces is essential for successful social interactions and good quality of life. Age-related macular degeneration (AMD) is a progressive eye condition that damages central vision required to see faces clearly. This thesis aims to investigate potential means to improve quality of life in AMD, via a two-pronged approach. The first prong examines the importance of face recognition difficulties, using a qualitative study of the effects of poor face perception in AMD on social interactions and quality of life. Previous studies of the impact of AMD on quality of life have focussed on domains including reading, driving, and self-care. Paper 1 of the thesis presents the first in-depth study of the quality-of-life impacts arising specifically from poor face perception. Results showed that, across all levels of vision loss (still driving through legally blind), AMD patients experience everyday problems with recognising who people are (face identity) and their emotions (facial expressions). These result in difficulties in social interactions, fear of offending others (e.g., appearing to ignore them deliberately), misinterpreting how others are feeling, and missing out in social situations. Patients also reported others did not understand their vision loss, and worried about appearing a fraud. These outcomes often contributed to social withdrawal and reduced confidence and quality of life. Paper 1 uses the study findings to develop new community resources (Faces and Social Life in AMD information sheet, conversation-starter, brochure for low-vision clinics), intended to improve patient and community understanding of how AMD affects face perception, and to provide practical tips for improving social interactions. The second prong focusses on improving face perception in AMD patients via image enhancement. The broad idea here is that, potentially, face images can be displayed to patients on screens or smart glasses after being digitally altered in ways that make them easier for patients to see and interpret. The specific image enhancement tested here is caricaturing, which involved exaggerating the shape information in the face image away from the average face (for face identity) or a neutral expression (for face expression). Paper 2 demonstrates that caricaturing can improve perception of identity in AMD; this benefit was observed for all eyes tested with mild vision loss, and half of eyes tested with moderate-to-severe vision loss. Paper 3 demonstrated that caricaturing can improve perception of facial expression in AMD, particularly for low-intensity expressions that are poorly recognised in their natural form, again across a wide range of vision loss. Overall, this thesis demonstrates that poor face perception in AMD is an important contributor to patients’ reduced quality of life. With the aim of enhancing quality of life, I have developed resources to improve community understanding, plus demonstrated that caricaturing provides a useful image enhancement method in AMD. Future research should focus on: further evaluation of the helpfulness of the community resources (to patients, carers and orthoptists); testing whether combining image enhancement methods (e.g., caricaturing plus contrast manipulations) can further improve face perception; and engineering advances needed to implement accurate caricaturing for patients in real-time.