Title: Suppression of positive emotions during pandemic era: a deep learning framework for rehabilitation

Authors: Ahona Ghosh; Sriparna Saha

Addresses: Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, West Bengal, India ' Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, West Bengal, India

Abstract: The rapidly growing popularity of computer and Android gaming in the pandemic era has led many researchers to focus on the emotional changes and adverse effects of gaming on a player. Sometimes games are played to give relaxation and help to recover from anxiety and stress, but some recent incidents are alarming since vigorous games playing can lead to anxiety and stress. This paper has attempted to overcome the shortcoming of existing literature by a novel approach to detect emotions acquired from electroencephalographic signals using a deep learning algorithm with high accuracy of emotion recognition. The feature extraction and classification algorithms individually outperformed the existing ones in the related area and the combination of them also has shown better performance than the state-of-the-art literature. Outcomes of the proposed framework have shown its wide range of applicability from parental control to cyber security by emotion detection and in terms can help in providing rehabilitation.

Keywords: deep learning; electroencephalogram; support vector machine; SVM; convolutional neural network; CNN; Chebyshev type I filter; cognitive rehabilitation; emotion management; pandemic era; circumplex model; android game.

DOI: 10.1504/IJMIC.2022.10052113

International Journal of Modelling, Identification and Control, 2022 Vol.41 No.1/2, pp.143 - 154

Received: 02 Jul 2021
Accepted: 20 Nov 2021

Published online: 22 Nov 2022 *

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