Description

Project Overview
This thesis project presents a unique opportunity for students to contribute to innovative research on adaptive RSVP (Rapid Serial Visual Presentation) systems, following up from [1]. The focus is on developing an intelligent RSVP system that adapts to user attention and cognitive load by leveraging pupil dilation data. Pupil dilation has been shown to correlate with cognitive processing, providing valuable insight into the user's mental state while reading or processing visual stimuli. By incorporating this biometric feedback into the RSVP system, the project aims to create a more intuitive and personalized reading experience, especially for users with attention challenges or disabilities.

Project Motivation

Traditional RSVP systems often rely on fixed speeds or manual adjustments, which may not suit every user's cognitive capacity. This project seeks to enhance user engagement and efficiency by using real-time pupil dilation data to adjust the speed and presentation style dynamically. By doing so, the RSVP system can become more responsive to individual reading habits, reducing cognitive overload and improving comprehension and retention of information. This work has important implications for accessibility, enabling better interaction for users with reading difficulties or neurological impairments.

Project Goals

This thesis will explore the development and evaluation of an adaptive RSVP system, with a focus on the following key objectives:

• Experiment Design: Participants will engage with an RSVP system where reading speeds are adjusted in real-time based on pupil dilation data, providing insights into the correlation between cognitive load and visual presentation speed.
• Model Development: Develop a model that interprets pupil dilation changes and optimizes the RSVP presentation in response to varying cognitive loads, ensuring that reading pace and comprehension are maximized.

You will

• Conduct a literature review on pupil dilation and cognitive load in relation to visual stimuli
• Develop or modify an RSVP system to integrate real-time pupil tracking data
• Implement a preprocessing pipeline to analyze pupil dilation data during RSVP tasks
• Collect and analyze data, focusing on how pupil dilation correlates with reading performance and user engagement
• Summarize findings in a thesis and present them to an audience
• (Optional) Co-write a research paper based on the results

You need

• Strong communication skills in English
• Experience with eye-tracking technologies and software
• Basic knowledge of machine learning for modeling data (e.g., Python, TensorFlow)

References

• [1] Grootjen, J., Thalhammer, P., & Kosch, T. (2024). Your eyes on speed: Using pupil dilation to adaptively select speed-reading parameters in virtual reality. In Proceedings of the 26th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '24). ACM. https://doi.org/10.1145/3676531