Comparison of Human Emotion Classification on Single-Channel and Multi-Channel EEG using Gate Recurrent Unit Algorithm

Yuri Pamungkas*, Ulfi Widya Astuti

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The use of EEG to recognize human emotions has become a notable trend and breakthrough today. EEG-based emotion recognition is a form of research that uses biomedical signals to distinguish a person's psychological condition (without directly paying attention to changes in facial gestures and attitudes). However, there are many studies related to emotion recognition whose classification accuracy is still low and needs to be improved. Therefore, we propose an EEG-based recognition of positive and negative emotions in this study using the Gate Recurrent Unit (GRU) algorithm. EEG data were taken from 38 participants with four recording channels (FP1, FP2, F7, and F8). In EEG recording, a video was played to stimulate the participants' emotions (positive and negative). Then, the EEG data is processed by filtering, artefact removal, frequency band decomposition, feature extraction, and emotion classification based on signal features. Several classification scenarios (such as by varying the activation function of the classifier and the number of EEG channels) are carried out to obtain an optimal level of accuracy. Based on the emotion classification results (using the Softmax activation function) on multi-channel EEG, the accuracy values reached 98.85% (for training) and 91.45% (for testing).

Original languageEnglish
Title of host publicationICCoSITE 2023 - International Conference on Computer Science, Information Technology and Engineering
Subtitle of host publicationDigital Transformation Strategy in Facing the VUCA and TUNA Era
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages375-380
Number of pages6
ISBN (Electronic)9798350320954
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Computer Science, Information Technology and Engineering, ICCoSITE 2023 - Jakarta, Indonesia
Duration: 16 Feb 2023 → …

Publication series

NameICCoSITE 2023 - International Conference on Computer Science, Information Technology and Engineering: Digital Transformation Strategy in Facing the VUCA and TUNA Era

Conference

Conference2023 International Conference on Computer Science, Information Technology and Engineering, ICCoSITE 2023
Country/TerritoryIndonesia
CityJakarta
Period16/02/23 → …

Keywords

  • EEG-based emotion recognition
  • Gate Recurrent Unit algorithm
  • band decomposition
  • emotion classification
  • feature extraction

Fingerprint

Dive into the research topics of 'Comparison of Human Emotion Classification on Single-Channel and Multi-Channel EEG using Gate Recurrent Unit Algorithm'. Together they form a unique fingerprint.

Cite this