A potential approach for emotion prediction using heart rate signals

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.