A Model-Based Approach for Extracting Emotional Status From Immobilized Beings Using EEG Signals

Human-computer interaction is a potential area of interest since the birth of the computer era. The chapter highlights the usage of electroencephalogram (EEG wave) signals to initiate a conveying medium for immobilized persons, who are not able to express their feelings, by the use of human brain waves or signals. In order to recognize the human feelings or expressions with some emotion by an disable persons, a classifier based on a gamma distribution is utilized. The characteristic of the human brain waves are extracted with the usage of cepstral coefficients. The extracted characteristic is classified into various emotion states using generalized gamma distribution. In order to experiment the proposed model, six healthy persons or subjects are taken aged between from 20 and 28, and a 64 electrode channel EEG system is considered to gather the EEG brain signals under audio as well as visual stimuli. In this chapter, the authors focused the study on four basic human emotions: boredom, sad, happy, and neutral.