The use of eye movements in human-computer interaction techniques: what you look at is what you get
ACM Transactions on Information Systems (TOIS) - Special issue on computer—human interaction
A robust algorithm for reading detection
Proceedings of the 2001 workshop on Perceptive user interfaces
A Hybrid Fuzzy Approach for Human Eye Gaze Pattern Recognition
Advances in Neuro-Information Processing
Keyboard before Head Tracking Depresses User Success in Remote Camera Control
INTERACT '09 Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II
Gaze pattern and reading comprehension
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
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This paper presents a study that investigates the connection between the way that people read and the way that they understand content. The experiment consisted of having participants read some information on selected documents while an eye-tracking system recorded their eye movements. They were then asked to answer some questions and complete some tasks, on the information they had read. With the intention of investigating effective analysis approaches, both statistical methods and Artificial Neural Networks (ANN) were applied to analyse the collected gaze data in terms of several defined measures regarding the relevance of the text. The results from the statistical analysis do not show any significant correlations between those measures and the relevance of the text. However, good classification results were obtained by using an Artificial Neural Network. This suggests that using advanced learning approaches may provide more insightful differentiations than simple statistical methods particularly in analysing eye gaze reading patterns.