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

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 vice-versa 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%.