research-article

Correlation Indices of Electroencephalogram-Based Relative Powers during Human Emotion Processing

Authors:

Noor Kamal Al-Qazzaz,

Mohannad K. Sabir,

Karl GrammerAuthors Info & Claims

ICBET '19: Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology

Pages 64 - 70

https://doi.org/10.1145/3326172.3326179

Published: 28 March 2019 Publication History

Abstract

The present study sought to employ audio-visual video clip stimuli to explore the electroencephalography-based (EEG) correlation between various emotional states. To that end, seven short video clips were shown to ten volunteer participants without health conditions whilst emotional EEG data were captured. The method of independent component analysis and wavelets (AICA-WT) was adopted for screening the extracted data. The correlation indices were computed based on spectral features employing the relative powers (RP) of delta (ΔRP), theta (θRP), alpha (αRP), beta (βRP), and gamma (γRP). The next step was calculation of Pearson's correlation between the of the neutral state and the of the six fundamental emotional states (i.e. anger, anxiety, disgust, happiness, sadness and surprise) of every EEG channel for different brain areas (i.e. frontal, temporal, parietal and occipital scalp). According to the findings obtained, the correlation of brain activity and emotional states among the brain areas observable in healthy EEG data can be investigated based on the relevant indices afforded by the new denoising method alongside EEG-based correlation analysis of the RP.

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Cited By

Al-Qazzaz NAli SAhmad S(2024)Verbesserung der Erkennung des Arbeitsgedächtnisses von Demenz-Patienten mithilfe von Entropie-basierten Merkmalen und dem Local Tangent Space Alignment AlgorithmusFortschritte in der nicht-invasiven biomedizinischen Signalverarbeitung mit ML10.1007/978-3-031-52856-9_14(381-411)Online publication date: 18-May-2024
https://doi.org/10.1007/978-3-031-52856-9_14
Al-Qazzaz NLafta RKhudhair M(2024)Schätzungen von emotionalen Synchronisationsindizes für Gehirnregionen mithilfe der Elektroenzephalogramm-SignalanalyseFortschritte in der nicht-invasiven biomedizinischen Signalverarbeitung mit ML10.1007/978-3-031-52856-9_13(349-380)Online publication date: 18-May-2024
https://doi.org/10.1007/978-3-031-52856-9_13
Al-Qazzaz NAli SAhmad S(2023)Recognition Enhancement of Dementia Patients’ Working Memory Using Entropy-Based Features and Local Tangent Space Alignment AlgorithmAdvances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning10.1007/978-3-031-23239-8_14(345-373)Online publication date: 23-Feb-2023
https://doi.org/10.1007/978-3-031-23239-8_14
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Index Terms

Correlation Indices of Electroencephalogram-Based Relative Powers during Human Emotion Processing
1. Applied computing
  1. Life and medical sciences
    1. Bioinformatics

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ICBET '19: Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology

March 2019

327 pages

ISBN:9781450361309

DOI:10.1145/3326172

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 28 March 2019

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ICBET ' 19

ICBET ' 19: 2019 9th International Conference on Biomedical Engineering and Technology

March 28 - 30, 2019

Tokyo, Japan

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Cited By

Al-Qazzaz NAli SAhmad S(2024)Verbesserung der Erkennung des Arbeitsgedächtnisses von Demenz-Patienten mithilfe von Entropie-basierten Merkmalen und dem Local Tangent Space Alignment AlgorithmusFortschritte in der nicht-invasiven biomedizinischen Signalverarbeitung mit ML10.1007/978-3-031-52856-9_14(381-411)Online publication date: 18-May-2024
https://doi.org/10.1007/978-3-031-52856-9_14
Al-Qazzaz NLafta RKhudhair M(2024)Schätzungen von emotionalen Synchronisationsindizes für Gehirnregionen mithilfe der Elektroenzephalogramm-SignalanalyseFortschritte in der nicht-invasiven biomedizinischen Signalverarbeitung mit ML10.1007/978-3-031-52856-9_13(349-380)Online publication date: 18-May-2024
https://doi.org/10.1007/978-3-031-52856-9_13
Al-Qazzaz NAli SAhmad S(2023)Recognition Enhancement of Dementia Patients’ Working Memory Using Entropy-Based Features and Local Tangent Space Alignment AlgorithmAdvances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning10.1007/978-3-031-23239-8_14(345-373)Online publication date: 23-Feb-2023
https://doi.org/10.1007/978-3-031-23239-8_14
Al-Qazzaz NLafta RKhudhair M(2023)Estimations of Emotional Synchronization Indices for Brain Regions Using Electroencephalogram Signal AnalysisAdvances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning10.1007/978-3-031-23239-8_13(315-344)Online publication date: 23-Feb-2023
https://doi.org/10.1007/978-3-031-23239-8_13
Al-Qazzaz NSabir MBin Mohd Ali SAhmad SGrammer K(2021)Complexity and Entropy Analysis to Improve Gender Identification from Emotional-Based EEGsJournal of Healthcare Engineering10.1155/2021/85370002021(1-17)Online publication date: 21-Sep-2021
https://doi.org/10.1155/2021/8537000
Liu ZNi FLi RZhang HLiu CZhang JXie S(2021)Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition ProcessJournal of Healthcare Engineering10.1155/2021/23343322021(1-11)Online publication date: 1-Nov-2021
https://doi.org/10.1155/2021/2334332
Al-Qazzaz NSabir MAli SAhmad SGrammer K(2021)Multichannel Optimization With Hybrid Spectral- Entropy Markers for Gender Identification Enhancement of Emotional-Based EEGsIEEE Access10.1109/ACCESS.2021.30964309(107059-107078)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3096430
Al-Qazzaz NSabir MAli SAhmad SGrammer K(2019)Electroencephalogram Profiles for Emotion Identification over the Brain Regions Using Spectral, Entropy and Temporal BiomarkersSensors10.3390/s2001005920:1(59)Online publication date: 20-Dec-2019
https://doi.org/10.3390/s20010059

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