Eye movement and pupillary response abnormalities measured using virtual reality as biomarkers in the diagnosis of early-stage Parkinson's disease.

Objective: Characteristic ocular symptoms are expected to serve as potential biomarkers for early diagnosis of Parkinson's disease (PD). However, possible ocular impairments in PD patients are rarely studied. The study aimed to investigate eye movement characteristics and pupil diameter changes in early-stage PD patients using virtual reality (VR)-based system and explore their contribution in the diagnosis of early-stage PD. Methods: Forty-three early-stage PD patients and 25 healthy controls were included. Eye movements and pupillary response of all subjects were recorded and evaluated by wearing VR glasses. All subjects completed pro-saccade and anti-saccade tasks. Saccadic eye movement and pupillary response parameters were analyzed. Random Forests method was used for classification task, the performance of the classification model in differentiating early-stage PD patients from healthy controls were evaluated. Results: PD patients exhibited reduced pro-saccade velocity and accuracy, longer average time to complete the pro-saccade, and lower anti-saccade error correction rate than healthy controls (all Conclusion: This study presents a non-invasive approach toward the diagnosis of early-stage PD with VR technology. Eye movement and pupillary response abnormalities measured using VR may be used as effective biomarkers for the diagnosis of early-stage PD.