Details

Improving Concussion Diagnosis with Visual Eye Tracking and Ocular EMG Analysis

Year: 2024

Term: Fall

Student Name: Precious Kolawole

Supervisor: Nadine Moacdieh / Andy Adler

Abstract: Eye tracking is becoming recognized as a tool in the diagnosis of concussion, having stepped up where older methods like Vestibular Ocular Motor Screening (VOMS) fall short. VOMS can make symptoms worse because it relies on patients reporting how they feel, which can be quite subjective. In this work, we expanded into the realm of eye tracking by analyzing eye movements during saccadic and calibration tasks through computer science techniques. We used peak detection, exponential curve fitting, tau and error rate analysis to quantitatively assess how closely a subject's eye trace aligns with established ground truths. Additionally, we implemented a time alignment software to correct temporal discrepancies between the eye movements of different subjects or with the ground truth. These implementations combine principles from both computer science and biology while providing precision and objectivity to concussion diagnosis through advanced eye tracking data analysis.