Emotion recognition in human computer interaction systems

Abstract

In order to ensure comfortable life human computer interaction (HCI) systems are widely used in the smart home. It is important to detect and respond to the smart home residents' emotional state and reduce stress levels. The HCI system for emotional state recognition is developed. This paper deals with stressful state recognition by means of the heart rate variability (HRV) analysis, because it is a noninvasive method. The emotional state should be identified in the situations which correspond to real life at home: a person sits, walks, and changes his/her posture over time. The impact of the emotional state and the posture impact on heart rate variability are examined. Time domain, frequency domain and nonlinear parameters are calculated. The parameters that are most sensitive to the emotional state are chosen. Variability of the HRV parameters are verified over time. It was found that posture has a great impact on the HRV parameters, so posture detection subsystem is integrated in our HCI system for emotion recognition. The subject- dependent thresholds should be used for emotional state recognition.