Identifying fixations and saccades in eye-tracking protocols
ETRA '00 Proceedings of the 2000 symposium on Eye tracking research & applications
Full-time wearable headphone-type gaze detector
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Eye Tracking Methodology: Theory and Practice
Eye Tracking Methodology: Theory and Practice
Rapid Prototyping of Activity Recognition Applications
IEEE Pervasive Computing
Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography
Pervasive '08 Proceedings of the 6th International Conference on Pervasive Computing
Wearable EOG goggles: Seamless sensing and context-awareness in everyday environments
Journal of Ambient Intelligence and Smart Environments
Head-mounted eye-tracking of infants' natural interactions: a new method
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Qualitative and quantitative scoring and evaluation of the eye movement classification algorithms
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Toward Mobile Eye-Based Human-Computer Interaction
IEEE Pervasive Computing
Eye Movement Analysis for Activity Recognition Using Electrooculography
IEEE Transactions on Pattern Analysis and Machine Intelligence
Guiding attention in controlled real-world environments
Proceedings of the ACM Symposium on Applied Perception
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Pervasive healthcare is a promising field of research as small and unobtrusive on-body sensors become available. However, despite considerable advances in the field, current systems are limited in terms of the pathologies they can detect, particularly regarding mental disorders. In this work we propose wearable eye tracking as a new method for mental health monitoring. We provide two reviews: one of the state-of-the-art in wearable eye tracking equipment and a second one of the work in experimental psychology and clinical research on the link between eye movements and cognition. Both reviews show a significant potential of wearable eye tracking for mental health monitoring in daily life settings. This finding calls for further research on unobtrusive sensing equipment and novel algorithms for automated analysis of long-term eye movement data.