Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/84767
Title: EEG-based valence level recognition for real-time applications
Authors: Liu, Yisi.
Sourina, Olga.
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Source: Liu, Y.,& Sourina, O. (2012). EEG-based Valence Level Recognition for Real-Time Applications. 2012 International Conference on Cyberworlds, 53-60.
Abstract: Emotions are important in human-computer interaction. Emotions could be classified based on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of emotions even without discrete emotion labels. In this paper, we proposed a real-time EEG-based subject-dependent valence level recognition algorithm, where the thresholds were used to identify different levels of the valence dimension of the human emotion. The algorithm was tested by using the EEG data labeled with valence levels. The algorithm could identify valence levels continuously. The algorithm was tested with the experiment data and with the benchmark affective EEG database DEAP where up to 9 levels of valence dimension with high/low dominance were recognized. Then, the algorithm was applied to recognize 16 emotions defined by high/low arousal, high/low dominance and 4 levels of valence. At least 14 electrodes should be used to get the better accuracy. The proposed algorithm could be implemented in different real-time applications such as emotional avatar and E-learning systems.
URI: https://hdl.handle.net/10356/84767
http://hdl.handle.net/10220/12706
DOI: 10.1109/CW.2012.15
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

SCOPUSTM   
Citations

16
Updated on Sep 2, 2020

PublonsTM
Citations

16
Updated on Feb 23, 2021

Page view(s)

316
Updated on Feb 25, 2021

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.