Brain wavesclassification towardhuman emotion based on EEG signal

The important role of communication between human’s brain and computer has been increased during the last years. In this research, the main focus of this thesis isanalysingbrain wavesthat associated with the internal emotion of human. The analysing processis achieved by reading the EEG signals from...

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Main Author:	Ahmed, Mohammed Abdulkareem
Format:	Thesis
Language:	English
Published:	2013
Subjects:	TK7885-7895 Computer engineer Computer hardware
Online Access:	http://eprints.utm.my/id/eprint/39015/5/MohammedAbdulkareemMFSKSM2013.pdf
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id	my-utm-ep.39015
record_format	uketd_dc
spelling	my-utm-ep.390152017-07-18T06:18:10Z Brain wavesclassification towardhuman emotion based on EEG signal 2013-05 Ahmed, Mohammed Abdulkareem TK7885-7895 Computer engineer. Computer hardware The important role of communication between human’s brain and computer has been increased during the last years. In this research, the main focus of this thesis isanalysingbrain wavesthat associated with the internal emotion of human. The analysing processis achieved by reading the EEG signals from user brain.NIA deviceis used in this research to read the signals from the frontal lobe of the brain. This sturdy base on reading brain wave signals in order to be representedas an avatar facial expression. The aim of this research is to show the influence of alpha and beta brain waves toward emotion classification through EEG signal. In addition,the researchis analysing brain signals in order to represent happy and sad emotions. The classification of human emotion through brain computer interface can be interpreted through speed of brain waves signal. The velocity is used to calculate the speed of brain signals for each emotion. The results provedthat the velocity of sad emotion is faster than happy emotion. As a conclusion, this research shows the speed for each emotion which can be used to specify the internal emotion characteristic of a user. User emotion is represented as a facial expression of virtual human in 3D environment. These results can be used to create a good classification because it specifies the average of speed for each emotion. 2013-05 Thesis http://eprints.utm.my/id/eprint/39015/ http://eprints.utm.my/id/eprint/39015/5/MohammedAbdulkareemMFSKSM2013.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK7885-7895 Computer engineer Computer hardware
spellingShingle	TK7885-7895 Computer engineer Computer hardware Ahmed, Mohammed Abdulkareem Brain wavesclassification towardhuman emotion based on EEG signal
description	The important role of communication between human’s brain and computer has been increased during the last years. In this research, the main focus of this thesis isanalysingbrain wavesthat associated with the internal emotion of human. The analysing processis achieved by reading the EEG signals from user brain.NIA deviceis used in this research to read the signals from the frontal lobe of the brain. This sturdy base on reading brain wave signals in order to be representedas an avatar facial expression. The aim of this research is to show the influence of alpha and beta brain waves toward emotion classification through EEG signal. In addition,the researchis analysing brain signals in order to represent happy and sad emotions. The classification of human emotion through brain computer interface can be interpreted through speed of brain waves signal. The velocity is used to calculate the speed of brain signals for each emotion. The results provedthat the velocity of sad emotion is faster than happy emotion. As a conclusion, this research shows the speed for each emotion which can be used to specify the internal emotion characteristic of a user. User emotion is represented as a facial expression of virtual human in 3D environment. These results can be used to create a good classification because it specifies the average of speed for each emotion.
format	Thesis
qualification_level	Master's degree
author	Ahmed, Mohammed Abdulkareem
author_facet	Ahmed, Mohammed Abdulkareem
author_sort	Ahmed, Mohammed Abdulkareem
title	Brain wavesclassification towardhuman emotion based on EEG signal
title_short	Brain wavesclassification towardhuman emotion based on EEG signal
title_full	Brain wavesclassification towardhuman emotion based on EEG signal
title_fullStr	Brain wavesclassification towardhuman emotion based on EEG signal
title_full_unstemmed	Brain wavesclassification towardhuman emotion based on EEG signal
title_sort	brain wavesclassification towardhuman emotion based on eeg signal
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2013
url	http://eprints.utm.my/id/eprint/39015/5/MohammedAbdulkareemMFSKSM2013.pdf
_version_	1747816538991230976

Brain wavesclassification towardhuman emotion based on EEG signal

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