Modeling the 2D space of emotions based on the poincare plot of heart rate variability signal

Abstract

Emotions mean accepting, understanding, and recognizing something with one's senses. The physiological signals generated from the internal organs of the body can objectively and realistically reflect changes in real-time human emotions and monitor the state of the body. In this study, the two-dimensional space-based emotion model was introduced on the basis of Poincare's two-dimensional plot of the signal of heart rate variability. Four main colors of psychology, blue, red, green, and yellow were used as a stimulant of emotion, and the ECG signals from 70 female students were recorded. Using extracted features of Poincare plot and heart rate asymmetry, two tree based models estimated the levels of arousal and valence with 0.05 mean square errors, determined an appropriate estimation of these two parameters of emotion. In the next stage of the study, four different emotions mean pleasure, anger, joy, and sadness, were classified using IF-THEN rules with the accuracy of 95.71%. The results show the color red is associated with more excitement and anger, while green has small anxiety. So, this system provides a measure for numerical comparison of mental states and makes it possible to model emotions for interacting with the computer and control mental states independently of the pharmaceutical methods.