Vision-Based Assistive Technologies for People with Cerebral Visual Impairment: A Review and Focus Study

TL;DR

This paper reviews existing vision-based assistive technologies and highlights a significant research gap in supporting individuals with Cerebral Visual Impairment, emphasizing the need for targeted HCI solutions.

Contribution

It identifies the lack of research on CVI in assistive tech and presents focus studies that explore challenges and opportunities specific to this demographic.

Findings

Research gap in CVI assistive technologies

Focus studies with 7 participants highlight specific needs

Call for targeted HCI research for CVI support

Abstract

Over the past decade, considerable research has investigated Vision-Based Assistive Technologies (VBAT) to support people with vision impairments to understand and interact with their immediate environment using machine learning, computer vision, image enhancement, and/or augmented/virtual reality. However, this has almost totally overlooked a growing demographic: people with Cerebral Visual Impairment (CVI). Unlike ocular vision impairments, CVI arises from damage to the brain's visual processing centres. Through a scoping review, this paper reveals a significant research gap in addressing the needs of this demographic. Three focus studies involving 7 participants with CVI explored the challenges, current strategies, and opportunities for VBAT. We also discussed the assistive technology needs of people with CVI compared with ocular low vision. Our findings highlight the opportunity for the Human-Computer Interaction and Assistive Technologies research community to explore and address this underrepresented domain, thereby enhancing the quality of life for people with CVI.