C. K. Lee, S. K. Yoo, Y. J. Park, N. H. Kim, K. S. Jeong and B. C. Lee, “Using Neural Network to Recognize Human Emotions from Heart Rate Variability and Skin Resistance,” 27th Annual Conference on Engineering in Medicine and Biology, Shanghai, 17-18 January 2006, pp. 5523-5525.

has been cited by the following article:

• TITLE: Emotions States Recognition Based on Physiological Parameters by Employing of Fuzzy-Adaptive Resonance Theory

  AUTHORS: Mahdis Monajati, Seyed Hamidreza Abbasi, Fereidoon Shabaninia, Sina Shamekhi

  KEYWORDS: Physiological Signal; Galvanic Skin Response; Heart Rate; Respiration Rate; Fuzzy-ART; Emotion Recognition

  JOURNAL NAME: International Journal of Intelligence Science, Vol.2 No.4A, November 1, 2012

  ABSTRACT: This paper is an investigation on negative emotions states recognition by employing of Fuzzy Adaptive Resonance Theory (Fuzzy-ART) considering the changes in activities of autonomic nervous system (ANS). Specific psychological experiments were designed to induce appropriate physiological responses on individuals in order to acquire a suitable database for training, validating and testing the proposed procedure. In this research, the three physiological applied signals are Galvanic Skin Response (GSR), Heart Rate (HR) and Respiration Rate (RR). The first experiment which is named Shock was designed to determine a criterion for the change of physiological signals of each individual. In the second one, a combination of two sets of questions has been asked from the subjects to induce their emotions. Finally, Physiological responses were analyzed by Fuzzy-ART to recognize which question excites the negative emotions. Detecting negative emotions from neutral is obtained with total accuracy of 94%.