Ophtalmic Diagnostics Using Eye Tracking Technology

Abstract

Human eyes directly reflect brain activity and cognition. The study of eye movements and gaze patterns can therefore say a lot about the human brain and human behavior. Today eye tracking technology is being used to measure acuity of toddlers, to rehabilitate patients in intensive care, to detect if a person is lying or not, and to understand the cognitive level of a non-verbal person. Current vision testing is mostly based on manual observation and subjective methods. With eye tracking technology eye movements can be tested in an automated way that increases reliability and reduces variability and subjectivity. Eye tracking technology allows for measuring eye movements and therefore quantitative comparisons of the progress in treatment can be made over the course of a patient¿s therapy ¿ enabling more effective therapy. This technology also enables standardized and automated processes that are more time- and cost-efficient. The most important advantages of this technology is that it is non-invasive and it is not necessary to stabilize the subject¿s head during testing. These advantages greatly extend the set of subjects that can be studied and reduce the cost and skills required for studying eye movements and gaze patterns. This thesis has developed and evaluated a novel calibration procedure for an eye tracker. The development phase has included programming and integration with the existing application programming interfaces. The evaluation phase included reliability and validity testing, as well as statistical analysis in terms of repeatability, objectivity, comprehension, relevance, and independence of the performance of the Tobii T60/T120 Eye Tracker on healthy subjects. The experimental results have shown that the prototype application gives the expected benefits in a clinical setting. A conclusion of this thesis is that eye tracking technology could be an improvement over existing methods for screening of eye alignment and diagnostics of ophthalmic disorders, such as strabismus (crossed eyes) or amblyopia (lazy eye). However, applying this technology to clinical cases will require further development. This development is suggested as future work.