IMPACT OF EMOTION IN HUMAN BRAIN-A LOBE-BASED ACTIVITY ON STRENGTH OF SIGNALS ANALYZED IN TWO FREQUENCY BANDS
Keywords:
emotion, ICA, kmean, unsupervised learning technique, brain lobesAbstract
Emotion analysis is an emerging field among current researchers. Emotion plays an important role in forming behavioural patterns in the human brain. A study was conducted in objective time space evolution of emotions. For emotion recognition, an EEG [electroencephalogram] data base was created from equal number of male and female subjects and named Amrita-emote database [ADB]. The subjects were shown videos of various emotions and simultaneously the output EEG signals were recorded into ADB, which contained 500 samples of data. Our study had focused into 5 basic emotions, Viz. neutral, happy, disgust, sad and fear. The ADB was split into two different frequency bands of 12-35 Hz as high frequency band [HFB] and 1-8Hz as low frequency band [LFB] for time localized responses. The time and space evolutions were studied by segmenting and K-mean clustering. For each emotion, the frequency distribution contributes from four regions in the brain. The statistical analysis was done to find the average contribution for each emotion.