Disabled person emotion recognition in EEG signal using deep neural network
by M.S. Pradeep Kumar; Krishnappa Suresh
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 19, No. 3/4, 2021

Abstract: Emotion recognition is an important field of research in brain-computer interactions. As technology and the understanding of emotions are advancing, there are growing opportunities for automatic emotion recognition systems. The brain uses the neuromuscular channels to communicate and control its external environment, however many disorders can disrupt these channels. An electroencephalogram (EEG) signals are generated in the human brain, communicate with several neurons and low amplitude signals. In this paper, the hybrid feature extraction (Renyi and differential entropy) was performed on the acquired EEG signal in order to achieve feature subsets. The respective feature values were given as the input for a multi-objective classifier: deep neural network (DNN) for classifying the disabled persons and their emotions. The proposed technique improves the emotion prediction accuracy for different sessions. The emotional recognition classification model includes three states: positive, neutral and negative. In experimental analysis, the proposed approach classifies the disabled persons and their emotions by means of specificity, sensitivity, and accuracy. The experimental outcome shows that the proposed methodology improved accuracy in emotion classification up to 8.01% compared to the existing methods: k-nearest neighbours (KNN) and support vector machine (SVM).

Online publication date: Wed, 21-Jul-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com