Entropy-AWARE Instrumentation for Just-In-Time Anomalous Human Behaviour Interventions

SENSATE aims at modeling anomalous human behavior via ubiquitous instrumentation sensing. The goal is to explore the contextual vectors that may lead to depressive behavior, a collaborative effort with UCLA Depression Grand Challenge and the European Alliance Against Depression with the largest scale of depression patients (100,000+) and linking with 2 Infotech top projects: Prof. Zhao’s micro-expressions and Prof. Lopez's vision-based physiological health assessment methods.

Traditionally, emotional and affective data is qualitative or subjective (e.g., questionnaires, diaries). Micro-expressions could provide invaluable and timely objective data on the current emotional state. Physiological health measurements augment emotional states with wellbeing and affective states. Both are correlated (e.g., we may be sick and therefore more tired or stressed), thus fully bridging SENSATE with these top projects. Having a real-world large dataset for methods’ validation will result in the highest quality research outcome.