AI RESEARCH
A Neuro-Symbolic System for Interpretable Multimodal Physiological Signals Integration in Human Fatigue Detection
arXiv CS.LG
•
ArXi:2603.24358v1 Announce Type: cross We propose a neuro-symbolic architecture that learns four interpretable physiological concepts, oculomotor dynamics, gaze stability, prefrontal hemodynamics, and multimodal, from eye-tracking and neural hemodynamics, functional near-infrared spectroscopy, (fNIRS) windows using attention-based encoders, and combines them with differentiable approximate reasoning rules using learned weights and soft thresholds, to address both rigid hand-crafted rules and the lack of subject-level alignment diagnostics.