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

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

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Official URL: http://dx.doi.org/10.1016/j.matpr.2021.10.190


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.

Item Type:Article
Uncontrolled Keywords:Brain Computer Interface (BCI), Electro-Encephalograph (EEG), emotion, machine learning, recognition
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Razak School of Engineering and Advanced Technology
ID Code:101172
Deposited By: Yanti Mohd Shah
Deposited On:01 Jun 2023 09:32
Last Modified:01 Jun 2023 09:32

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