Emotion recognition based on pressure sensor keyboards

This paper describes a new approach to emotion recognition based on pressure sensor keyboards. The pressure sensor keyboard is a new product that occurs in the market recently, which produces a pressure sequence when keystroke occurs. The analysis of the pressure sequence should be a novel research area. It has been used for identity verification in our previous research. In this paper, we use the pressure sequence for emotion recognition. Three methods (global features of pressure sequences, dynamic time warping and traditional keystroke dynamics) are proposed for the emotion recognition task; then we combined the three methods together using a classifier fusion technique. Several experiments were performed on a database containing 3000 samples (from 50 individuals, including six emotions: neutral, anger, fear, happiness, sadness and surprise) and the best result were achieved utilizing all the method, obtaining an overall accuracy of 93.4%. Our technique of emotion recognition has been used for intelligent game controlling and several other applications.