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Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers

Identifying emotions has become essential for comprehending varied human behavior during our daily lives. The electroencephalogram (EEG) has been adopted for eliciting information in terms of waveform distribution over the scalp. The rationale behind this work is twofold. First, it aims to propose s...

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Main Authors: Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Md. Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl
Format: Article
Language:English
Published: MDPI 2020
Online Access:http://psasir.upm.edu.my/id/eprint/38199/1/38199.pdf
http://psasir.upm.edu.my/id/eprint/38199/
https://www.mdpi.com/1424-8220/20/1/59
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spelling my.upm.eprints.381992020-05-04T15:52:28Z http://psasir.upm.edu.my/id/eprint/38199/ Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers Al-Qazzaz, Noor Kamal Sabir, Mohannad K. Md. Ali, Sawal Hamid Ahmad, Siti Anom Grammer, Karl Identifying emotions has become essential for comprehending varied human behavior during our daily lives. The electroencephalogram (EEG) has been adopted for eliciting information in terms of waveform distribution over the scalp. The rationale behind this work is twofold. First, it aims to propose spectral, entropy and temporal biomarkers for emotion identification. Second, it aims to integrate the spectral, entropy and temporal biomarkers as a means of developing spectro-spatial (SS) , entropy-spatial (ES) and temporo-spatial (TS) emotional profiles over the brain regions. The EEGs of 40 healthy volunteer students from the University of Vienna were recorded while they viewed seven brief emotional video clips. Features using spectral analysis, entropy method and temporal feature were computed. Three stages of two-way analysis of variance (ANOVA) were undertaken so as to identify the emotional biomarkers and Pearson’s correlations were employed to determine the optimal explanatory profiles for emotional detection. The results evidence that the combination of applied spectral, entropy and temporal sets of features may provide and convey reliable biomarkers for identifying SS, ES and TS profiles relating to different emotional states over the brain areas. EEG biomarkers and profiles enable more comprehensive insights into various human behavior effects as an intervention on the brain. MDPI 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/38199/1/38199.pdf Al-Qazzaz, Noor Kamal and Sabir, Mohannad K. and Md. Ali, Sawal Hamid and Ahmad, Siti Anom and Grammer, Karl (2020) Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers. Sensors, 20 (1). art. no. 59. pp. 1-21. ISSN 1424-8220 https://www.mdpi.com/1424-8220/20/1/59 10.3390/s20010059
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Identifying emotions has become essential for comprehending varied human behavior during our daily lives. The electroencephalogram (EEG) has been adopted for eliciting information in terms of waveform distribution over the scalp. The rationale behind this work is twofold. First, it aims to propose spectral, entropy and temporal biomarkers for emotion identification. Second, it aims to integrate the spectral, entropy and temporal biomarkers as a means of developing spectro-spatial (SS) , entropy-spatial (ES) and temporo-spatial (TS) emotional profiles over the brain regions. The EEGs of 40 healthy volunteer students from the University of Vienna were recorded while they viewed seven brief emotional video clips. Features using spectral analysis, entropy method and temporal feature were computed. Three stages of two-way analysis of variance (ANOVA) were undertaken so as to identify the emotional biomarkers and Pearson’s correlations were employed to determine the optimal explanatory profiles for emotional detection. The results evidence that the combination of applied spectral, entropy and temporal sets of features may provide and convey reliable biomarkers for identifying SS, ES and TS profiles relating to different emotional states over the brain areas. EEG biomarkers and profiles enable more comprehensive insights into various human behavior effects as an intervention on the brain.
format Article
author Al-Qazzaz, Noor Kamal
Sabir, Mohannad K.
Md. Ali, Sawal Hamid
Ahmad, Siti Anom
Grammer, Karl
spellingShingle Al-Qazzaz, Noor Kamal
Sabir, Mohannad K.
Md. Ali, Sawal Hamid
Ahmad, Siti Anom
Grammer, Karl
Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers
author_facet Al-Qazzaz, Noor Kamal
Sabir, Mohannad K.
Md. Ali, Sawal Hamid
Ahmad, Siti Anom
Grammer, Karl
author_sort Al-Qazzaz, Noor Kamal
title Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers
title_short Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers
title_full Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers
title_fullStr Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers
title_full_unstemmed Electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers
title_sort electroencephalogram profiles for emotion identification over the brain regions using spectral, entropy and temporal biomarkers
publisher MDPI
publishDate 2020
url http://psasir.upm.edu.my/id/eprint/38199/1/38199.pdf
http://psasir.upm.edu.my/id/eprint/38199/
https://www.mdpi.com/1424-8220/20/1/59
_version_ 1665895963221295104
score 13.211869

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