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Analyzing recognition of EEG based human attention and emotion using machine learning

An emotionally recognised area of research has already been quite prominent. EEG brain signals have recently been used to recognise an individual's mental condition. Attention often plays a key role in human development, but needs more study. This article offers a noble method of acknowledgment...

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Main Authors: Alam, Mohammad Shabbir, A. Jalil, Siti Zura, Upreti, Kamal
Format: Article
Published: Elsevier Ltd 2022
Subjects:
QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/101172/
http://dx.doi.org/10.1016/j.matpr.2021.10.190
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spelling my.utm.1011722023-06-01T09:32:00Z http://eprints.utm.my/id/eprint/101172/ Analyzing recognition of EEG based human attention and emotion using machine learning Alam, Mohammad Shabbir A. Jalil, Siti Zura Upreti, Kamal QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering An emotionally recognised area of research has already been quite prominent. EEG brain signals have recently been used to recognise an individual's mental condition. Attention often plays a key role in human development, but needs more study. This article offers a noble method of acknowledgment of human attention by sophisticated machine learning algorithms. Scalp-EEG signalling is a cost-effective, single-swinged mechanism dependent on time. Many trials have shown possible support for emotional identification through brain EEG waves. This paper examines and suggests a modern technology for the identification of emotions through the application of new computer learning principles. Ablations experiments also demonstrate the clear and important benefit to the efficiency of our RGNN model from the adjacent matrix and two regularizers. Finally, neuronal researches reveal key brain regions and inter-channel relationships for EEG related emotional awareness. Elsevier Ltd 2022 Article PeerReviewed Alam, Mohammad Shabbir and A. Jalil, Siti Zura and Upreti, Kamal (2022) Analyzing recognition of EEG based human attention and emotion using machine learning. Materials Today: Proceedings, 56 (6). pp. 3349-3354. ISSN 2214-7853 http://dx.doi.org/10.1016/j.matpr.2021.10.190 DOI:10.1016/j.matpr.2021.10.190
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
Alam, Mohammad Shabbir
A. Jalil, Siti Zura
Upreti, Kamal
Analyzing recognition of EEG based human attention and emotion using machine learning
description An emotionally recognised area of research has already been quite prominent. EEG brain signals have recently been used to recognise an individual's mental condition. Attention often plays a key role in human development, but needs more study. This article offers a noble method of acknowledgment of human attention by sophisticated machine learning algorithms. Scalp-EEG signalling is a cost-effective, single-swinged mechanism dependent on time. Many trials have shown possible support for emotional identification through brain EEG waves. This paper examines and suggests a modern technology for the identification of emotions through the application of new computer learning principles. Ablations experiments also demonstrate the clear and important benefit to the efficiency of our RGNN model from the adjacent matrix and two regularizers. Finally, neuronal researches reveal key brain regions and inter-channel relationships for EEG related emotional awareness.
format Article
author Alam, Mohammad Shabbir
A. Jalil, Siti Zura
Upreti, Kamal
author_facet Alam, Mohammad Shabbir
A. Jalil, Siti Zura
Upreti, Kamal
author_sort Alam, Mohammad Shabbir
title Analyzing recognition of EEG based human attention and emotion using machine learning
title_short Analyzing recognition of EEG based human attention and emotion using machine learning
title_full Analyzing recognition of EEG based human attention and emotion using machine learning
title_fullStr Analyzing recognition of EEG based human attention and emotion using machine learning
title_full_unstemmed Analyzing recognition of EEG based human attention and emotion using machine learning
title_sort analyzing recognition of eeg based human attention and emotion using machine learning
publisher Elsevier Ltd
publishDate 2022
url http://eprints.utm.my/id/eprint/101172/
http://dx.doi.org/10.1016/j.matpr.2021.10.190
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score 13.211869

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