Paralympic Movement meets Eye Movements

This thesis investigates how eye-tracking technology can be used to improve the assessment of visual function in individuals with vision impairment, with a special focus on its application in para sports. The main goal is to develop an eye movement-based test that enhances the current classification system used for athletes with vision impairment. Classification in this context aims to ensure fair competition by grouping athletes based on the extent to which their impairment affects sport performance. Traditional assessments rely heavily on measures like visual acuity, which may not fully capture functional limitations. This research proposes eye-tracking as a more objective, sensitive, and standardized tool for this purpose. The research is divided into three key steps, explored across four studies. Step 1 focuses on the development of a suitable eye movement test for individuals with vision impairment. Chapter 2 reviews existing literature, confirming that eye-tracking is feasible across various ocular conditions but noting a lack of data on certain impairments that may affect tracking quality. Five key eye movement tests are identified as useful for assessing visual function. In Chapter 3, these are integrated into a new test battery that includes individuals with a broad range of impairments, avoiding exclusion based on eye conditions. The study confirms that the test is valid and sensitive in distinguishing between different levels and types of visual function. Step 2 examines whether impaired eye movements, as measured by the test battery, are related to sport performance—a necessary condition for including these measures in athlete classification. Chapter 3 demonstrates that eye-tracking data can predict real-world sport performance in athletes with vision impairment, and does so more effectively when combined with visual acuity. This suggests that eye-tracking captures dimensions of visual function that traditional tests miss. Chapter 4 builds on this by investigating how different types of impairment affect eye movement strategies during a real-time tennis task. It reveals that athletes adopt unique, impairment-specific gaze strategies, enabling them to perform effectively despite significant vision loss. These findings underline the relevance of eye-tracking metrics in understanding how vision impairment impacts functional performance. Step 3 addresses the issue of intentional misrepresentation—when athletes exaggerate their impairment for competitive advantage. Chapter 5 introduces Fitts’ law, which predicts a linear relationship between task difficulty and movement time. If this relationship breaks down, it may suggest submaximal effort. The study tests whether Fitts’ law holds under simulated vision impairment and finds that, for some eye movement metrics, the relationship persists or even strengthens with increased impairment. This indicates that Fitts’ law could serve as a tool for detecting intentional misrepresentation in athletes with vision impairment. In conclusion, this thesis establishes eye-tracking as a powerful tool for improving athlete classification in para sports. Beyond sports, it offers a novel method for assessing visual function in a more functionally relevant way. Eye-tracking has the potential to enhance fairness in competition, improve clinical assessment, and offer new strategies for detecting misrepresentation—paving the way for more effective support and evaluation of individuals with vision impairment.