The clinical observation and assessment of extra-ocular movements is common practice in assessing neurodegenerative disorders but remains observer-dependent. In the present study, we propose an algorithm that can automatically identify saccades, fixation, smooth pursuit, and blinks using a non-invasive eye tracker. Subsequently, response-to-stimuli-derived interpretable features were elicited that objectively and quantitatively assess patient behaviors.
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