Classification of EEG Spectrogram Using ANN for IQ Application

The intelligence term can be view in many areas such as linguistic, mathematical, music and art. In this paper, the Intelligence Quotient (IQ) is measured using Electroencephalogram (EEG) from the human brain. The spectrogram images were formed from EEG signals, then th...

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Main Authors:	Mahfuzah, Mustafa, Norizam, Sulaiman
Format:	Conference or Workshop Item
Language:	English
Published:	2013
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/3794/ http://umpir.ump.edu.my/id/eprint/3794/2/fkee_mahfuzah_2013.pdf

id	ump-3794
recordtype	eprints
spelling	ump-37942017-10-25T08:03:10Z http://umpir.ump.edu.my/id/eprint/3794/ Classification of EEG Spectrogram Using ANN for IQ Application Mahfuzah, Mustafa Norizam, Sulaiman TK Electrical engineering. Electronics Nuclear engineering The intelligence term can be view in many areas such as linguistic, mathematical, music and art. In this paper, the Intelligence Quotient (IQ) is measured using Electroencephalogram (EEG) from the human brain. The spectrogram images were formed from EEG signals, then the Gray Level Co-occurrence Matrix (GLCM) texture feature were extracted from the images. This texture feature produced big matrix data, thus Principal Component Analysis (PCA) is used to reduce the big matrix. Then, ANN algorithm is employed to classify the EEG spectrogram image in IQ application. The results will be validated based on the concept of Raven's Standard Progressive Matrices (RPM) IQ test. The results showed that the ANN was able to classify the EEG spectrogram image with 88.89% accuracy and 0.0633 MSE 2013 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/3794/2/fkee_mahfuzah_2013.pdf Mahfuzah, Mustafa and Norizam, Sulaiman (2013) Classification of EEG Spectrogram Using ANN for IQ Application. In: The International Conference on Technological Advances in Electrical, Electronics and Computer Engineering, 9-11 Mei 2013 , Mevlana University, Turki. . (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Mahfuzah, Mustafa Norizam, Sulaiman Classification of EEG Spectrogram Using ANN for IQ Application
description	The intelligence term can be view in many areas such as linguistic, mathematical, music and art. In this paper, the Intelligence Quotient (IQ) is measured using Electroencephalogram (EEG) from the human brain. The spectrogram images were formed from EEG signals, then the Gray Level Co-occurrence Matrix (GLCM) texture feature were extracted from the images. This texture feature produced big matrix data, thus Principal Component Analysis (PCA) is used to reduce the big matrix. Then, ANN algorithm is employed to classify the EEG spectrogram image in IQ application. The results will be validated based on the concept of Raven's Standard Progressive Matrices (RPM) IQ test. The results showed that the ANN was able to classify the EEG spectrogram image with 88.89% accuracy and 0.0633 MSE
format	Conference or Workshop Item
author	Mahfuzah, Mustafa Norizam, Sulaiman
author_facet	Mahfuzah, Mustafa Norizam, Sulaiman
author_sort	Mahfuzah, Mustafa
title	Classification of EEG Spectrogram Using ANN for IQ Application
title_short	Classification of EEG Spectrogram Using ANN for IQ Application
title_full	Classification of EEG Spectrogram Using ANN for IQ Application
title_fullStr	Classification of EEG Spectrogram Using ANN for IQ Application
title_full_unstemmed	Classification of EEG Spectrogram Using ANN for IQ Application
title_sort	classification of eeg spectrogram using ann for iq application
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/3794/ http://umpir.ump.edu.my/id/eprint/3794/2/fkee_mahfuzah_2013.pdf
first_indexed	2023-09-18T21:58:18Z
last_indexed	2023-09-18T21:58:18Z
_version_	1777414228128301056

Classification of EEG Spectrogram Using ANN for IQ Application

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