• Register
  • Login

European Journal of Molecular & Clinical Medicine

  • Home
  • Browse
    • Current Issue
    • By Issue
    • By Subject
    • Keyword Index
    • Author Index
    • Indexing Databases XML
  • Journal Info
    • About Journal
    • Aims and Scope
    • Editorial Board
    • Publication Ethics
    • Indexing and Abstracting
    • Peer Review Process
    • News
  • Guide for Authors
  • Submit Manuscript
  • Contact Us
Advanced Search

Notice

As part of Open Journals’ initiatives, we create website for scholarly open access journals. If you are responsible for this journal and would like to know more about how to use the editorial system, please visit our website at https://ejournalplus.com or
send us an email to info@ejournalplus.com

We will contact you soon

  1. Home
  2. Volume 7, Issue 8
  3. Author

Online ISSN: 2515-8260

Volume7, Issue8

Electroencephalogram Based Emotion Detection Using Hybrid LongShort Term Memory

    Thejaswini S, Dr. K M Ravikumar

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 8, Pages 2786-2792

  • Show Article
  • Download
  • Cite
  • Statistics
  • Share

Abstract

Emotion detection using physiological signals is an upcoming research extending applications in various domains. One important challenge in detection of inner emotion states is a good predictive rate in order to build any application. In our present work, a hybrid Long Short Term Memory (LSTM) algorithm is proposed based on channel fusion approach. Data is acquired by eliciting emotions using eight 3-D Virtual Reality (VR) videos for eight discrete emotion states. On preprocessed data, 8-level decomposition using Discrete Wavelet Transforms(DWT) is performed, wavelet features and time-domain features are extracted and fed to Hybrid LSTM. The hybrid algorithm is performing well for eight discrete emotion states (happy excited, calm, bored, fear, tensed, sad and relax), with an accuracy rate of 80.05% and 93.24 % for 4 states in categorical form (Valence- Arousal scale). Frequency domain features on various bands exhibited a good predictive rate than time domain features.
Keywords:
  • PDF (283 K)
  • XML
(2020). Electroencephalogram Based Emotion Detection Using Hybrid LongShort Term Memory. European Journal of Molecular & Clinical Medicine, 7(8), 2786-2792.
Thejaswini S, Dr. K M Ravikumar. "Electroencephalogram Based Emotion Detection Using Hybrid LongShort Term Memory". European Journal of Molecular & Clinical Medicine, 7, 8, 2020, 2786-2792.
(2020). 'Electroencephalogram Based Emotion Detection Using Hybrid LongShort Term Memory', European Journal of Molecular & Clinical Medicine, 7(8), pp. 2786-2792.
Electroencephalogram Based Emotion Detection Using Hybrid LongShort Term Memory. European Journal of Molecular & Clinical Medicine, 2020; 7(8): 2786-2792.
  • RIS
  • EndNote
  • BibTeX
  • APA
  • MLA
  • Harvard
  • Vancouver
  • Article View: 95
  • PDF Download: 306
  • LinkedIn
  • Twitter
  • Facebook
  • Google
  • Telegram
Journal Information

Publisher:

Email:  editor.ejmcm21@gmail.com

  • Home
  • Glossary
  • News
  • Aims and Scope
  • Privacy Policy
  • Sitemap

 

For Special Issue Proposal : editor.ejmcm21@gmail.com

This journal is licensed under a Creative Commons Attribution 4.0 International (CC-BY 4.0)

Powered by eJournalPlus