Open AccessIQ Classification via Brainwave Features: Review on Artificial Intelligence Techniques
Author(s) -
A. H. Jahidin,
Mohd Nasir Taib,
Nooritawati Md Tahir,
Megat Syahirul Amin Megat Ali
Publication year - 2015
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v5i1.pp84-91
Subject(s) - computer science , artificial intelligence , feature selection , feature (linguistics) , attention span , machine learning , cognition , pattern recognition (psychology) , psychology , philosophy , linguistics , neuroscience
Intelligence study is one of keystone to distinguish individual differences in cognitive psychology. Conventional psychometric tests are limited in terms of assessment time, and existence of biasness issues. Apart from that, there is still lack in knowledge to classify IQ based on EEG signals and intelligent signal processing (ISP) technique. ISP purpose is to extract as much information as possible from signal and noise data using learning and/or other smart techniques. Therefore, as a first attempt in classifying IQ feature via scientific approach, it is important to identify a relevant technique with prominent paradigm that is suitable for this area of application. Thus, this article reviews several ISP approaches to provide consolidated source of information. This in particular focuses on prominent paradigm that suitable for pattern classification in biomedical area. The review leads to selection of ANN since it has been widely implemented for pattern classification in biomedical engineering.