RAEMAP: Real-Time Advanced Eye Movements Analysis Pipeline

Abstract

Eye-tracking measures enable means to understand the underlying covert processes engaged during inhibitory tasks which rely on attention allocation. We propose Real-Time Advanced Eye Movements Analysis Pipeline (RAEMAP) to utilize eye tracking measures as a valid psychophysiological measure. RAEMAP will include realtime analysis of the traditional positional gaze metrics as well as advanced metrics such as ambient/focal coefficient κ, gaze transition entropy, and index of pupillary activity (IPA). RAEMAP will also provide visualizations of calculated eye gaze metrics, heatmaps, and dynamic AOI generation in real-time. This paper will outline the proposed architecture of RAEMAP in terms of distributed computing, incorporation of machine learning models, and the evaluation to prove the utility of RAEMAP to diagnose ADHD in real-time.