Single trial EEG patterns for the prediction of individual differences in fluid intelligence

Assessing a person’s intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in oddball task and fluid intelligence score are correlated because both reflect the cognitive processing and attention. A system for prediction of an in...

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Main Authors: Qazi, E.-H., Hussain, M., Aboalsamh, H., Malik, A.S., Ullahamin, H., Bamatraf, S.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.19649 /
Published: Frontiers Media S. A 2017
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010871730&doi=10.3389%2ffnhum.2016.00687&partnerID=40&md5=baf631d6935b4512da6d64719f8be77a
http://eprints.utp.edu.my/19649/
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spelling utp-eprints.196492018-04-20T07:24:47Z Single trial EEG patterns for the prediction of individual differences in fluid intelligence Qazi, E.-H. Hussain, M. Aboalsamh, H. Malik, A.S. Ullahamin, H. Bamatraf, S. Assessing a person’s intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in oddball task and fluid intelligence score are correlated because both reflect the cognitive processing and attention. A system for prediction of an individual’s fluid intelligence level using single trial Electroencephalography (EEG) signals has been proposed. For this purpose, we employed 2D and 3D contents and 34 subjects each for 2D and 3D, which were divided into low-ability (LA) and high-ability (HA) groups using Raven's Advanced Progressive Matrices (RAPM) test. Using visual oddball cognitive task, neural activity of each group was measured and analyzed over three midline electrodes (Fz, Cz, and Pz). To predict whether an individual belongs to LA or HA group, features were extracted using wavelet decomposition of EEG signals recorded in visual oddball task and support vector machine (SVM) was used as a classifier. Two different types of Haar wavelet transform based features have been extracted from the band (0.3 to 30 Hz) of EEG signals. Statistical wavelet features and wavelet coefficient features from the frequency bands 0.0–1.875 Hz (delta low) and 1.875–3.75 Hz (delta high), resulted in the 100 and 98 prediction accuracies, respectively, both for 2D and 3D contents. The analysis of these frequency bands showed clear difference between LA and HA groups. Further, discriminative values of the features have been validated using statistical significance tests and inter-class and intra-class variation analysis. Also, statistical test showed that there was no effect of 2D and 3D content on the assessment of fluid intelligence level. Comparisons with state-of-the-art techniques showed the superiority of the proposed system. © 2017 Qazi, Hussain, Aboalsamh, Malik, Amin and Bamatraf. Frontiers Media S. A 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010871730&doi=10.3389%2ffnhum.2016.00687&partnerID=40&md5=baf631d6935b4512da6d64719f8be77a Qazi, E.-H. and Hussain, M. and Aboalsamh, H. and Malik, A.S. and Ullahamin, H. and Bamatraf, S. (2017) Single trial EEG patterns for the prediction of individual differences in fluid intelligence. Frontiers in Human Neuroscience, 10 . http://eprints.utp.edu.my/19649/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Assessing a person’s intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in oddball task and fluid intelligence score are correlated because both reflect the cognitive processing and attention. A system for prediction of an individual’s fluid intelligence level using single trial Electroencephalography (EEG) signals has been proposed. For this purpose, we employed 2D and 3D contents and 34 subjects each for 2D and 3D, which were divided into low-ability (LA) and high-ability (HA) groups using Raven's Advanced Progressive Matrices (RAPM) test. Using visual oddball cognitive task, neural activity of each group was measured and analyzed over three midline electrodes (Fz, Cz, and Pz). To predict whether an individual belongs to LA or HA group, features were extracted using wavelet decomposition of EEG signals recorded in visual oddball task and support vector machine (SVM) was used as a classifier. Two different types of Haar wavelet transform based features have been extracted from the band (0.3 to 30 Hz) of EEG signals. Statistical wavelet features and wavelet coefficient features from the frequency bands 0.0–1.875 Hz (delta low) and 1.875–3.75 Hz (delta high), resulted in the 100 and 98 prediction accuracies, respectively, both for 2D and 3D contents. The analysis of these frequency bands showed clear difference between LA and HA groups. Further, discriminative values of the features have been validated using statistical significance tests and inter-class and intra-class variation analysis. Also, statistical test showed that there was no effect of 2D and 3D content on the assessment of fluid intelligence level. Comparisons with state-of-the-art techniques showed the superiority of the proposed system. © 2017 Qazi, Hussain, Aboalsamh, Malik, Amin and Bamatraf.
format Article
author Qazi, E.-H.
Hussain, M.
Aboalsamh, H.
Malik, A.S.
Ullahamin, H.
Bamatraf, S.
spellingShingle Qazi, E.-H.
Hussain, M.
Aboalsamh, H.
Malik, A.S.
Ullahamin, H.
Bamatraf, S.
Single trial EEG patterns for the prediction of individual differences in fluid intelligence
author_sort Qazi, E.-H.
title Single trial EEG patterns for the prediction of individual differences in fluid intelligence
title_short Single trial EEG patterns for the prediction of individual differences in fluid intelligence
title_full Single trial EEG patterns for the prediction of individual differences in fluid intelligence
title_fullStr Single trial EEG patterns for the prediction of individual differences in fluid intelligence
title_full_unstemmed Single trial EEG patterns for the prediction of individual differences in fluid intelligence
title_sort single trial eeg patterns for the prediction of individual differences in fluid intelligence
publisher Frontiers Media S. A
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010871730&doi=10.3389%2ffnhum.2016.00687&partnerID=40&md5=baf631d6935b4512da6d64719f8be77a
http://eprints.utp.edu.my/19649/
_version_ 1741196240791535616
score 11.62408

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