A Decision Theoretic Model for Stress Recognition and User Assistance

Book One

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 20

Human-Computer Interaction

We present a general unified probabilistic decisiontheoretic model based on Influence Diagrams for simultaneously modeling both user stress recognition and user assistance. Stress recognition is achieved through dynamic probabilistic inference from the available sensory data from multiple-modality sources. User assistance is automatically achieved by balancing the benefits of improving user performance and the costs of performing user assistance. In addition, a non-invasive real-time system is built to validate the proposed framework. Utilizing the evidences from four modalities (physical appearance features, physiological measures, user performance and behavioral data), the system can successfully recognize human stress and provide timely and appropriate assistance in a task-specific environment.