Affiliation:
1. AVN Institute of Engineering and Technology, Hyderabad, India
2. Vignan Institute of Technology and Science, Hyderabad, India
3. Institute of Aeronautical Engineering, Hyderabad, India
Abstract
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.
Reference13 articles.
1. Cai. (2009). The Research on Emotion Recognition from ECG Signal. Academic Press.
2. Chen. (2000). Emotional Expressions in Audiovisual Human Computer Interaction. Academic Press.
3. Krishna. (2019). An Efficient Mixture Model Approach in Brain-Machine Interface Systems for Extracting the Psychological Status of Mentally Impaired Persons Using EEG Signals. IEEE Access.
4. Inferring the Human Emotional State of Mind using Asymetric Distrubution;N.Krishna;International Journal of Advanced Computer Science and Applications,2013
5. A Novel Approach for Effective Emotion Recognition Using Double Truncated Gaussian Mixture Model and EEG