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Projects -> Health Assessment

Goal: Find eye movement-based biomarkers that allow accurately and reliably assess various health states in a person.

Motivation: Many health conditions manifest themselves in the degradation of the function of the Human Visual System. Existing technologies frequently require expensive measuring devices and a time-consuming visit to a doctor to find out the onset of a specific condition. We would like to identify a subset of eye movement-based biomarkers that can signal different health conditions even by an inexpensive eye tracking device and a fast eye movement test. Employment of Ocular Biometric framework that takes into account individual eye movement signature of a person targets to increase the accuracy of health assessment.

Project Status: Looking for students interested in the project. The students will participate in the eye movement recording, data analysis, and creating algorithms for health assessment.


D. J. Lohr, E. Abdulin, and O. V. Komogortsev, Detecting the onset of eye fatigue in a live framework, In Proceedings of the ACM Symposium on Eye Tracking Research & Applications (ETRA 2016), 2016, pp. 1-2. [.pdf]

E. Abdulin and O. V. Komogortsev, User Eye Fatigue Detection via Eye Movement Behavior, In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), 2015, pp. 1-6. [.pdf]

O. V. Komogortsev and C. Holland, The Application of Eye Movement Biometrics in the Automated Detection of Mild Traumatic Brain Injury, In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), 2014, pp. 1-6. [.pdf]

D. Gobert and O. Komogortsev, Computerized Assessment of Oculomotor Dysfunction in Persons with mTBI 8th World Congress on Brain Injury, Washington, DC, March 10-14, 2010. [link]