MFCC for robust emotion detection using EEG

This paper proposes an emotion recognition system based on the Mel Frequency Cepstral coefficient (MFCC) of the bio-signals. Using gathered data under psychological emotion stimulation experiments, 4 types of emotions, happy, fear, sad and calm are classified. MLP is used as the classifiers. Experimental results show potential of using this technique to verify emotion based on the EEG signals of accuracy up to 90% can be achieved. This shows the potential of using the MFCC-MLP approach to detect basic emotions using EEG signals from the brain scalp.