부산대학교 도서관

In this paper, we build an emotion prediction system by only using heart rate signals. This system can easily support any heart-rate ‘sensor and smartphone to enhance users’ experience. We collect heart-rate data from registered users from a heart-rate sensor by building an Android application, namely Emotion and Heart Rate Collection. We analyze different kinds of feature vectors and compare various supervised learning models, including k-Nearest Neighbor (kNN), Support Vector Machine (SVM), and decision tree. The experiments show that using SVM can achieve the highest performance in comparison with other approaches.