Emotion Recognition Measurement based on Physiological Signals

Emotion recognition plays an important part in interpersonal interaction, especially for Human-Computer Interaction (HCI). Emotions are not only tightly intertwined neurologically with the mechanisms responsible for cognition, but that they also play a pivotal role in decision making, problem solving, communicating, negotiating, and adapting to unpredictable environments. Emotions can be recognized by many measurements such as gesture, facial images, neuro imaging and physiological signals. Among which, the measurement based on physiological signals is considered as a more natural means of emotion recognition because the emotional status is inherently inflected in the activity of the nervous system. In the present paper, it was reviewed that the recent advancements in emotion recognition research using physiological signals, including emotion models and stimulation, signals preprocessing, feature extraction and classification methodologies. It would provide an insight on the current research progress, existing problems, and challenges of emotion recognition based on physiological signals.