What is it about?

Intelligence and learning styles are among most widely studied traits in cognitive psychology. We have shown that both traits of cognition can be assessed directly from the resting brain. The extracted power ratio features have been successfully implemented to assess cognitive behavior through a computational model that was developed using artificial neural network.

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Why is it important?

We have successfully 1) standardized EEG recording protocol, signal processing and feature extraction techniques, 2) demonstrated the relationship between intelligence and learning style through EEG power ratio pattern, and 3) developed an intelligent computational model for assessing both traits of cognition with excellent performance.


This article has the potential to reach collaborators from the field of psychological assessment. The study provides an alternative and unbiased method for assessing IQ levels and learning styles. Implementation of such system increases efficacy as the standardized procedure reduces cost and assessment time. The relationship between intelligence and learning style has also been shown through the power ratio features in theta, alpha and beta bands.

Dr. Megat Syahirul Amin Megat Ali
Universiti Teknologi MARA

Read the Original

This page is a summary of: EEG-based intelligent system for cognitive behavior classification, Journal of Intelligent & Fuzzy Systems, July 2020, IOS Press,
DOI: 10.3233/jifs-190955.
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