This repository houses the code for our cognitive experiment aimed at analyzing user gaze points. By tracking and analyzing where users look during the experiment, we hope to gain insights into visual attention and cognitive processing.
In this experiment, participants are presented with various visual stimuli on a screen, and their gaze points are recorded in real-time. The objective is to understand how different elements within the stimuli influence the user's attention and how this might correlate with cognitive outcomes.
Features Real-time Gaze Tracking: Utilizes advanced eye-tracking technology to capture gaze data accurately. Data Analysis: Implements statistical and machine learning techniques to analyze gaze patterns and extract meaningful insights. Visualization: Includes scripts to generate visual representations of gaze data, helping to identify trends and areas of interest.