EEG based sensing of brain signals : emotional states classification - Heah, Dian Chuan. (2011)
Electroencephalogram (EEG) is one of the more popular and powerful tool used today to study of human brain activities and emotions. With the increasing trend of using communication tools, it will be desirable to explore in the area of emotions classification. The objective of this project is to use EEG to study the effectiveness of various classification algorithms for two emotional states of the brain signals, “Happy” and “Sad”. Data was collected from 5 subjects (males) using pictures from the International Affective Picture System (IAPS) as stimuli. A total of two trials were conducted for each subject with 30 pictures in each trial. The experiments conducted were meticulously designed to provide minimum artifacts’ interference and maximum quality of the data so as to ensure utmost reliability in the data collected. These are done by carefully designing the timings of the stimuli and taking extensive measures in the impedance reading of electrodes.