For neurodegenerative conditions like Parkinson's disease, early and accurate diagnosis is still a difficult task. Evaluations can be time consuming, patients must often travel to metropolitan areas or different cities to see experts, and misdiagnosis can result in improper treatment. To date, only a handful of assistive or remote methods exist to help physicians evaluate patients with suspected neurological disease in a convenient and consistent way. In this paper, we present a low-cost VR interface designed to support evaluation and diagnosis of neurodegenerative disease and test its use in a clinical setting. Using a commercially available VR display with an infrared camera integrated into the lens, we have constructed a 3D virtual environment designed to emulate common tasks used to evaluate patients, such as fixating on a point, conducting smooth pursuit of an object, or executing saccades. These virtual tasks are designed to elicit eye movements commonly associated with neurodegenerative disease, such as abnormal saccades, square wave jerks, and ocular tremor. Next, we conducted experiments with 9 patients with a diagnosis of Parkinson's disease and 7 healthy controls to test the system's potential to emulate tasks for clinical diagnosis. We then applied eye tracking algorithms and image enhancement to the eye recordings taken during the experiment and conducted a short follow-up study with two physicians for evaluation. Results showed that our VR interface was able to elicit five common types of movements usable for evaluation, physicians were able to confirm three out of four abnormalities, and visualizations were rated as potentially useful for diagnosis.
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