Journal
NEURAL COMPUTING & APPLICATIONS
Volume 26, Issue 6, Pages 1277-1296Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-014-1790-y
Keywords
Affective computing; Human emotion recognition; Keyboard keystroke dynamics; Mouse touch pad movement; Touch screen monitor; Human-computer interaction (HCI)
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Emotions play an important role in human interactions. They can be integrated into the computer system to make human-computer interaction (HCI) more effective. Affective computing is an innovative computational modeling and detecting user's emotions to optimize system responses in HCI. However, there is a trade-off between recognition accuracy and real-time performance in some of the methods such as processing the facial expressions, human voice and body gestures. Other methods lack efficiency and usability in real-world applications such as natural language processing and electroencephalography signals. To accomplish a reliable, usable and high-performance system, this paper proposes an intelligent hybrid approach to recognize users' emotions by using easily accessible and low computational cost input devices including keyboard, mouse (touch pad: single touch) and touch screen display (single touch). Using the proposed approach, the system is developed and trained in a supervised mode by artificial neural network and support vector machine (SVM) techniques. The result shows an increase in accuracy of 6 % (93.20 %) by SVM in comparison with the currently existing methods. It is a significant contribution to show new directions of future research in emotion recognition, user modeling and emotional intelligence.
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