EEG Spectrogram Classification Employing ANN for IQ Application
The term intelligence is associated in many areas such as linguistic, mathematical, music and art. In this paper, Intelligence Quotient (IQ) is measured using Electroencephalogram (EEG) from the human brain. The EEG signals are then used to form the spectrogram images, from which a large data of Gra...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/6313/ http://umpir.ump.edu.my/id/eprint/6313/1/EEG_spectrogram_classification_employing_ANN_for_IQ_application.pdf |
| _version_ | 1848817742720794624 |
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| author | Mahfuzah, Mustafa Mohd Nasir, Taib Sahrim, Lias Zunairah, Murat Norizam, Sulaiman |
| author_facet | Mahfuzah, Mustafa Mohd Nasir, Taib Sahrim, Lias Zunairah, Murat Norizam, Sulaiman |
| author_sort | Mahfuzah, Mustafa |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The term intelligence is associated in many areas such as linguistic, mathematical, music and art. In this paper, Intelligence Quotient (IQ) is measured using Electroencephalogram (EEG) from the human brain. The EEG signals are then used to form the spectrogram images, from which a large data of Gray Level Co-occurrence Matrix (GLCM) texture features were extracted. Then, Principal Component Analysis (PCA) is used to reduce the big matrix, and is followed with the classification of the EEG spectrogram image in IQ application using ANN algorithm. The results are then validated based on the concept of Raven's Standard Progressive Matrices (RPM) IQ test. The results showed that the ANN is able to classify the EEG spectrogram image with 88.89% accuracy and 0.0633 MSE. |
| first_indexed | 2025-11-15T01:26:36Z |
| format | Conference or Workshop Item |
| id | ump-6313 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T01:26:36Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-63132018-04-11T01:55:28Z http://umpir.ump.edu.my/id/eprint/6313/ EEG Spectrogram Classification Employing ANN for IQ Application Mahfuzah, Mustafa Mohd Nasir, Taib Sahrim, Lias Zunairah, Murat Norizam, Sulaiman TK Electrical engineering. Electronics Nuclear engineering The term intelligence is associated in many areas such as linguistic, mathematical, music and art. In this paper, Intelligence Quotient (IQ) is measured using Electroencephalogram (EEG) from the human brain. The EEG signals are then used to form the spectrogram images, from which a large data of Gray Level Co-occurrence Matrix (GLCM) texture features were extracted. Then, Principal Component Analysis (PCA) is used to reduce the big matrix, and is followed with the classification of the EEG spectrogram image in IQ application using ANN algorithm. The results are then validated based on the concept of Raven's Standard Progressive Matrices (RPM) IQ test. The results showed that the ANN is 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/6313/1/EEG_spectrogram_classification_employing_ANN_for_IQ_application.pdf Mahfuzah, Mustafa and Mohd Nasir, Taib and Sahrim, Lias and Zunairah, Murat and Norizam, Sulaiman (2013) EEG Spectrogram Classification Employing ANN for IQ Application. In: Technological Advances In Electrical, Electronics And Computer Engineering (TAEECE) , 9-11 May 2013 , Konya. pp. 199-203.. (Published) http://dx.doi.org/10.1109/TAEECE.2013.6557222 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Mahfuzah, Mustafa Mohd Nasir, Taib Sahrim, Lias Zunairah, Murat Norizam, Sulaiman EEG Spectrogram Classification Employing ANN for IQ Application |
| title | EEG Spectrogram Classification Employing ANN for IQ Application |
| title_full | EEG Spectrogram Classification Employing ANN for IQ Application |
| title_fullStr | EEG Spectrogram Classification Employing ANN for IQ Application |
| title_full_unstemmed | EEG Spectrogram Classification Employing ANN for IQ Application |
| title_short | EEG Spectrogram Classification Employing ANN for IQ Application |
| title_sort | eeg spectrogram classification employing ann for iq application |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/6313/ http://umpir.ump.edu.my/id/eprint/6313/ http://umpir.ump.edu.my/id/eprint/6313/1/EEG_spectrogram_classification_employing_ANN_for_IQ_application.pdf |