Design and Implementation of Mobile Personal Emotion Monitoring System

It is suggested that emotion plays a significant role in rational and intelligent behaviors. People behave emotions in different ways, and may not be noticeable through outside appearances. However, physiological information may reveal the clue for emotions. We proposed a mobile personal emotion monitoring system design, and proposed an adaptive algorithm that can help recognize user's emotion stateby using physiological sensors. We applied the dimensional analysis approach and adopted IAPS (International Affective Picture System) to manipulate psychological experiments. We also proposed an emotion recognition learning algorithm. It would extract each pattern of emotions from cross validation training and can further learn adaptively by feeding personalized testing data. We measured the learning rate of each subject which reveals incremental enhancement. Furthermore, we adopted a dimensional to discrete emotion transforming concept for validating the subjective rating. Compared to the experiment results of related works, our system outperforms both in dimensional and discrete analyses. Most importantly, the system is implemented based on wireless physiological sensors for mobile usage. This system can reflect the image of emotion states in order to provide on-line smart services.