A multi-modal emotion recognition system for persistent and non-invasive personal health monitoring

Abstract

We present a multi-modal emotion recognition system for persistent and non-invasive personal health monitoring. Our system is capable of effectively estimating human emotional states through analyzing and fusing a number of non-invasive external cues (such as facial expression, body posture, and voice intonation) in a systematic way through utilizing a probabilistic information fusion model.