Correlation between stimulated emotion extracted from EEG and its manifestation on facial expression

Authors:
A. Chakraborty;P. Bhowmik;S. Das;A. Halder;A. K. Nagar
Affiliations:
Dept. of Computer Science and Engineering, St. Thomas' College of Engineering and Technology, Calcutta and;Dept. of Electronics and Tele-Communication Engg., Jadavpur University, Calcutta;Dept. of Electronics and Tele-Communication Engg., Jadavpur University, Calcutta;Dept. of Electronics and Tele-Communication Engg., Jadavpur University, Calcutta;Dept. of Computer Science, Liverpool Hope University, Liverpool, UK
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

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Abstract

Determining correlation between aroused emotion and its manifestation on facial expression, voice, gesture and posture have interesting applications in psychotherapy. A set of audiovisual stimulus, selected by a group of experts, is used to excite emotion of the subjects. EEG and facial expression of the subjects excited by the selected audio-visual stimulus are collected, and the nonlinear-correlation from EEG to facial expression, and viceversa is obtained by employing feed-forward neural network trained with back-propagation algorithm. Experiments undertaken reveals that the trained network can reproduce the correlated EEG-facial expression trained instances with 100 % accuracy, and is also able to predict facial expression (EEG) from unknown EEG (facial expression) of the same subject with an accuracy of around 95.2%.