The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy
  • Promote your Publication

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Indexing
  • Submit your Paper
  • Guidelines
  • Fees
  • Current Issue
  • Archives
  • Editors
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2017.080955

Classification of Human Emotions from Electroencephalogram (EEG) Signal using Deep Neural Network

Author 1: Abeer Al-Nafjan
Author 2: Manar Hosny
Author 3: Areej Al-Wabil
Author 4: Yousef Al-Ohali

PDF

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 9, 2017.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Estimation of human emotions from Electroencephalogram (EEG) signals plays a vital role in developing robust Brain-Computer Interface (BCI) systems. In our research, we used Deep Neural Network (DNN) to address EEG-based emotion recognition. This was motivated by the recent advances in accuracy and efficiency from applying deep learning techniques in pattern recognition and classification applications. We adapted DNN to identify human emotions of a given EEG signal (DEAP dataset) from power spectral density (PSD) and frontal asymmetry features. The proposed approach is compared to state-of-the-art emotion detection systems on the same dataset. Results show how EEG based emotion recognition can greatly benefit from using DNNs, especially when a large amount of training data is available.

Keywords: Electroencephalogram (EEG); Brain-Computer Interface (BCI); emotion recognition; affective state; Deep Neural Network (DNN); DEAP dataset

Abeer Al-Nafjan, Manar Hosny, Areej Al-Wabil and Yousef Al-Ohali, “Classification of Human Emotions from Electroencephalogram (EEG) Signal using Deep Neural Network” International Journal of Advanced Computer Science and Applications(IJACSA), 8(9), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080955

@article{Al-Nafjan2017,
title = {Classification of Human Emotions from Electroencephalogram (EEG) Signal using Deep Neural Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080955},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080955},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {9},
author = {Abeer Al-Nafjan and Manar Hosny and Areej Al-Wabil and Yousef Al-Ohali}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2024

4-5 April 2024

  • Berlin, Germany

Computing Conference 2024

11-12 July 2024

  • London, United Kingdom

IntelliSys 2024

5-6 September 2024

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2023

2-3 November 2023

  • San Francisco, United States
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org