GenEyePose: Patient-Free, Knowledge-Based Saccadic Eye Movement Modeling for Digital Neurophysiologic Biomarker Development
Researchers have developed GenEyePose, a novel pipeline for generating synthetic eye movement data to train AI models for neurophysiologic biomarker development. This approach addresses the scarcity of real-world clinical data and privacy concerns associated with eye-tracking studies. A deep learning classifier trained on this synthetic data demonstrated promising performance in distinguishing normal from abnormal saccadic eye movements, showing potential for clinical applications in screening and localization of brain abnormalities. AI
IMPACT Synthetic data generation for AI models could accelerate the development of accessible diagnostic tools for neurological conditions.