Detecting impaired vision caused by AMD from gaze data.

Abstract

Age Related Macular Degeneration (AMD) is the third leading cause of blindness and the first one in the elderly. AMD usually causes central blindness due to loss of photoreceptor cell . In this paper, we propose to detect AMD caused vision impairment from gaze data. Compared with the current methods, e.g., Amsler grid, Microperimetry and Preferential Hyperacuity Perimetry, to detect vision impairments, the proposed method has several advantages. 1) It does not require the patient to stare at a fixed position throughout the test. 2) It does not require the patient to orally or manually report / mark out the vision impairment. 3) It is easy to operate thus a trained nurse is capable of operating the test. We collect gaze data while the patient is performing fixation and smooth pursuit. Features describing the gaze properties are extracted and SVM with linear kernel is trained to detect AMD impaired vision. To implement the proposed method, we collected gaze data of 74 eyes of 57 patients, who are diagnosed as AMD patient by clinicians. Nidek Microperimetry is adopted as gold standard. 57 eyes with normal vision and 17 eyes with impaired vision (blind at more than half test points in Nidek test) are used for test. The result verifies the effectiveness of detecting vision impairment from gaze data.