Can your smartphone detect your emotion?

The smartphone has become an indispensable part in people's life. Identifying the user's emotional state according to the usage of smartphone is a new way to improve the human-computer interaction and user experience. In this paper, we present an attempt to recognize emotional states by using finger-stroke pattern. Firstly, International Affective Picture System (IAPS) were used to design the emotion inducing experiment. Then finger-stroke features under different emotional categories were extracted and analyzed. Ultimately, we used machine learning algorithms to identify three basic emotional states including positive, neutral, and negative. The experiment results show that the stroke exists some specific behavioral patterns between different people. For all 24 subjects, the average classification accuracy rate reached 85.1%, and we got the average recognition accuracy at 72.3%, 74.6% and 69.6% for male, female and all subjects.