Investigating the Impact of Simulated Cataracts on Eye Movements in Virtual Reality (Using Machine Learning)
BT/MT
Status | open |
Student | N/A |
Advisor | Jesse Grootjen |
Professor | Prof. Dr. Sven Mayer |
Task
Description
Cataracts, affecting 65.2 million globally, are a major visual impairment. This thesis explores challenges faced by individuals with age-related cataracts, focusing on differences in eye movements during simulated cataracts in virtual reality (VR) compared to normal or corrected vision. Building on prior research [3, 4], we will implement a cataract simulation in Unity, controlling parameters like visual acuity, contrast, color shift, dark shadows, and glaring lights. Unlike previous studies, our analysis will explore how these parameters affect task performance. We will employ machine learning on eye tracking and head movement data to discern differences between normal or corrected and impaired vision.
This work aims to establish a correlation between eye movements and cataract simulation parameters. Through semi-constructed interviews and self-reporting, we aim to identify when participants notice the simulated cataract, focusing subsequent data analysis on differences in eye movements. In conclusion, visual impairments, especially cataracts, impact everyday tasks. One outcome could be to suggest that deviations in eye movements can be detected before users notice visual changes, offering potential as an early indicator for visual impairments.
You will
- Perform a literature review
- Modify an existing VR environment
- Implement an preprocessing pipeline for eye-tracking data
- Collect and analyze eye-tracking data using Machine Learning
- Summarize your findings in a thesis and present them to an audience
- (Optional) co-writing a research paper
You need
- Strong communication skills in English
- Good knowledge of Unity
- Good knowledge of Python libraries for scientific computing (e.g. Scipy, SK Learn, Tensorflow, PyTorch).
References
- [1] World report on vision. Geneva: World Health Organization; 2019. Licence: CC BY-NC-SA 3.0 IGO.
- [2] Seddon, J., Fong, D., West, S. K., & Valmadrid, C. T. (1995). Epidemiology of risk factors for age-related cataract. Survey of ophthalmology, 39(4), 323-334.
- [3] Krösl, K. (2020). Simulating vision impairments in virtual and augmented reality (Doctoral dissertation, Wien).
- [4] Jones, P. R., & Ometto, G. (2018, March). Degraded reality: using VR/AR to simulate visual impairments. In 2018 IEEE Workshop on Augmented and Virtual Realities for Good (VAR4Good) (pp. 1-4). IEEE.