Identification of Ocular Biomarkers for the Development of an Early Stage Diagnostic Tool for Neurodegenerative Disease

Abstract

Current methods of diagnosis for neurodegenerative diseases are almost purely qualitative and highly apparent only when extensive neuronal dystrophy and degeneration have occurred. Therefore, creating a clinically viable tool that leverages early biomarkers of neurodegenerative disease is necessary. Past research indicates that ocular biomarkers are a potential source of quantitative assessment for the early diagnosis of neurodegenerative disease. In this paper, we identify specific ocular biomarkers that could be used as a basis for the early detection of neurodegenerative disease, potentially using machine learning techniques. Furthermore, we outline data collection procedures that can be implemented for patients completing Pro-Saccade, Anti-Saccade, Express-Saccadic, and Smooth Pursuit tasks. We expect that the findings in this paper can be utilized to guide the future creation of tools and datasets for developing a gaze-based diagnostic tool.