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IQ Classification via Brainwave Features: Review on Artificial Intelligence Techniques

Jahidin, Aisyah HartiniTaib, Mohd NasirMd Tahir, NooritawatiMegat Ali, Megat Syahirul Amin
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 Februari 2015
DOI10.11591/ijece.v5i1.pp84-91

Abstrak

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.

Kata Kunci

Biomedical, Signal Processing, Human IntelligenceEEG, IQ, ANN, Expert system, Fuzzy logic

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IQ Classification via Brainwave Features: Review on Artificial Intelligence Techniques | International Journal of Electrical and Computer Engineering (IJECE) | Publiora