DEAP Based Individual's Emotion Detection through Computed EEG and Facial Expression Analysis

Electronics and Communication Engineering

The study of changes in physiological signals for emotion recognition in human subjects has generated immense interest in medical instrumentation. One of the effective ways of classifying emotions is by the use of the event-related potential (ERPs) of electroencephalogram (EEG) signals. This requires projection of an image on one computer system while simultaneously putting a marker on another computer system acquiring the EEG. Emotion plays an important role in our daily life. Real-time assessment and regulation of emotions will improve people’s life and make it better. For example, in the communication of human –machine interaction, emotion recognition will make the process more easy. Another example, in the treatment of patients, especially those have expression problems, the real emotion state of patients will help doctors to provide them more appropriate medical care. Here we proposed a reliable method which efficient in detection of individual’s health like whether they are normal or abnormal by using two factors mainly. (1) Face Expression (2) EEG info. This design can detect the condition of the individual person using image classifier and EEG analyzer using adaptive threshold detection method.

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