Oculomotor-Pupillary AI Biomarkers in Parkinson's

The goal of this prospective observational study is to investigate whether oculomotor-pupillary abnormalities detected using a novel edge-AI eye-tracking device can serve as objective and quantitative biomarkers for the early screening and clinical evaluation of Parkinson's disease (PD). The study will include individuals with early-to-moderate PD and healthy controls. The main question it aims to answer is: Can oculomotor-pupillary abnormalities detected by a novel edge-AI eye-tracking device serve as objective and quantitative biomarkers for the early screening of Parkinson's disease? Researchers will compare oculomotor-pupillary parameters between participants with PD and healthy controls and evaluate the ability of these parameters to distinguish PD from healthy controls. Participants with PD will also be followed for 12 months to assess longitudinal changes in eye-tracking measures and their associations with clinical changes. Participants will: 1. Complete standardized eye-tracking tasks to assess oculomotor and pupillary function using the study eye-tracking device. 2. Undergo clinical assessments of motor function, cognitive function, and non-motor symptoms. 3. For participants with PD, attend follow-up assessments over 12 months to evaluate changes in eye-tracking and clinical measures. The study will also evaluate the feasibility and clinical application of the independently developed edge-AI eye-tracking system and develop and validate lightweight real-time models for PD classification and prediction of disease progression.