Effective EEG Channels for Emotion Identification over the Brain Regions using Differential Evolution Algorithm

Noor Kamal Al-Qazzaz, Mohannad K. Sabir, Sawal Ali, Siti Anom Ahmad, Karl Grammer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The motivation of this study was to detect the most effective electroencephalogram (EEG) channels for various emotional states of the brain regions (i.e. frontal, temporal, parietal and occipital). The EEGs of ten volunteer participants without health conditions were captured while the participants were shown seven, short, emotional video clips with audio (i.e. anger, anxiety, disgust, happiness, sadness, surprise and neutral). The Savitzky-Golay (SG) filter was adopted for smoothing and denoising the EEG dataset. The spectral features were performed by employing the relative spectral powers of delta (δRP), theta (θRP), alpha (αRP), beta (βRP), and gamma (γRP). The differential evolution-based channel selection algorithm (DEFS-Ch) was computed to find the most suitable EEG channels that have the greatest efficacy for identifying the various emotional states of the brain regions. The results revealed that all seven emotions previously mentioned were represented by at least two frontal and two temporal channels. Moreover, some emotional states could be identified by channels from the parietal region such as disgust, happiness and sadness. Furthermore, the right and left occipital channels may help in identifying happiness, sadness, surprise and neutral emotional states. The DEFS-Ch algorithm raised the linear discriminant analysis (LDA) classification accuracy from 80% to 86.85%, indicating that DEFS-Ch may offer a useful way for reliabl enhancement of the detection of different emotional states of the brain regions.

Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4703-4706
Number of pages4
ISBN (Electronic)9781538613115
DOIs
Publication statusPublished - Jul 2019
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany
Duration: 23 Jul 201927 Jul 2019

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
CountryGermany
CityBerlin
Period23/7/1927/7/19

Fingerprint

Electroencephalography
Happiness
Brain
Emotions
Parietal Lobe
Anger
Discriminant Analysis
Discriminant analysis
Surgical Instruments
Motivation
Volunteers
Anxiety
Health
Identification (Psychology)

Keywords

  • channel selection
  • differential evolution algorithm
  • electroencephalography
  • Emotion
  • relative power
  • Savitzky-Golay

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Al-Qazzaz, N. K., Sabir, M. K., Ali, S., Ahmad, S. A., & Grammer, K. (2019). Effective EEG Channels for Emotion Identification over the Brain Regions using Differential Evolution Algorithm. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 (pp. 4703-4706). [8856854] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2019.8856854

Effective EEG Channels for Emotion Identification over the Brain Regions using Differential Evolution Algorithm. / Al-Qazzaz, Noor Kamal; Sabir, Mohannad K.; Ali, Sawal; Ahmad, Siti Anom; Grammer, Karl.

2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 4703-4706 8856854 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Al-Qazzaz, NK, Sabir, MK, Ali, S, Ahmad, SA & Grammer, K 2019, Effective EEG Channels for Emotion Identification over the Brain Regions using Differential Evolution Algorithm. in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019., 8856854, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc., pp. 4703-4706, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, Berlin, Germany, 23/7/19. https://doi.org/10.1109/EMBC.2019.8856854
Al-Qazzaz NK, Sabir MK, Ali S, Ahmad SA, Grammer K. Effective EEG Channels for Emotion Identification over the Brain Regions using Differential Evolution Algorithm. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 4703-4706. 8856854. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2019.8856854
Al-Qazzaz, Noor Kamal ; Sabir, Mohannad K. ; Ali, Sawal ; Ahmad, Siti Anom ; Grammer, Karl. / Effective EEG Channels for Emotion Identification over the Brain Regions using Differential Evolution Algorithm. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 4703-4706 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).
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