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A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals

This paper elaborates about the analyzing of Intelligent Quotient (IQ) and Emotional Quotient (EQ) of an engineering student based on Electroencephalogram (EEG) or brain signals using a computing tool such as MATLAB. The influence of individual’s IQ and EQ on the development of innovative thinking i...

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Main Authors: Afiqah, Norsepri, Norizam, Sulaiman, Mahfuzah, Mustafa, Hasan, Md Mahmudul, Siti Armiza, Mohd Aris
Format: Article
Language:English
Published: Penerbit UMP 2023
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/40082/1/A%20Study%20of%20Engineering%20Student%20IQ%20and%20EQ.pdf
http://umpir.ump.edu.my/id/eprint/40082/
https://doi.org/10.15282/mekatronika.v5i2.9853
https://doi.org/10.15282/mekatronika.v5i2.9853
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spelling my.ump.umpir.400822024-01-18T04:28:32Z http://umpir.ump.edu.my/id/eprint/40082/ A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals Afiqah, Norsepri Norizam, Sulaiman Mahfuzah, Mustafa Hasan, Md Mahmudul Siti Armiza, Mohd Aris TK Electrical engineering. Electronics Nuclear engineering This paper elaborates about the analyzing of Intelligent Quotient (IQ) and Emotional Quotient (EQ) of an engineering student based on Electroencephalogram (EEG) or brain signals using a computing tool such as MATLAB. The influence of individual’s IQ and EQ on the development of innovative thinking is significant. An IQ alone is not adequate to measure the success of a person. An EQ somehow is found to have a substantial correlation with individual’s performance which shows that both IQ and EQ are important in determining the character and manner of individual’s thinking skills. The main objective of this project is to analyze the output of EEG signals produced by an engineering student based on their IQ and EQ level. A comparison of which quotient influences the student’s thinking skill is also observed in this study. In this project, a single channel EEG amplifier is used to record the EEG signals from 6 different subjects with three different conditions: while not doing anything, during an IQ test and during an EQ test. The data is recorded using the EEG sensors with Unicorn Recorder software that is connected to the amplifier while recording is run. The result of the experiment also explained in terms of the mean value and standard deviation of the EEG bands for each subject and condition. The results of the study conclude that the IQ level of an individual is affected by the Beta band of the EEG signals. Meanwhile, Alpha band of the EEG signals is more dominant in the determination of EQ level of an individual. When Alpha band is higher than Beta band, it shows that the subject is dominant to an EQ dominant person. If Beta band is higher than Alpha band, then IQ is the dominant quotient for the subject. The highest k-NN classification accuracy is obtained at 80:20 classification with 81.84% accuracy using Mean features and 79.53% accuracy using Standard Deviaton features. This study also included the development of Graphical User Interface (GUI) in MATLAB. The GUI is used for the classification of the chosen EEG features. Theta, Alpha, and Beta power band are observed from the EEG signals to identify brain activity. In addition, IQ and EQ analyzer is constructed using Arduino microcontroller once the analysis of the EEG signals are done through GUI. Penerbit UMP 2023-07 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/40082/1/A%20Study%20of%20Engineering%20Student%20IQ%20and%20EQ.pdf Afiqah, Norsepri and Norizam, Sulaiman and Mahfuzah, Mustafa and Hasan, Md Mahmudul and Siti Armiza, Mohd Aris (2023) A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 5 (2). pp. 57-66. ISSN 2637-0883. (Published) https://doi.org/10.15282/mekatronika.v5i2.9853 https://doi.org/10.15282/mekatronika.v5i2.9853
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Afiqah, Norsepri
Norizam, Sulaiman
Mahfuzah, Mustafa
Hasan, Md Mahmudul
Siti Armiza, Mohd Aris
A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals
description This paper elaborates about the analyzing of Intelligent Quotient (IQ) and Emotional Quotient (EQ) of an engineering student based on Electroencephalogram (EEG) or brain signals using a computing tool such as MATLAB. The influence of individual’s IQ and EQ on the development of innovative thinking is significant. An IQ alone is not adequate to measure the success of a person. An EQ somehow is found to have a substantial correlation with individual’s performance which shows that both IQ and EQ are important in determining the character and manner of individual’s thinking skills. The main objective of this project is to analyze the output of EEG signals produced by an engineering student based on their IQ and EQ level. A comparison of which quotient influences the student’s thinking skill is also observed in this study. In this project, a single channel EEG amplifier is used to record the EEG signals from 6 different subjects with three different conditions: while not doing anything, during an IQ test and during an EQ test. The data is recorded using the EEG sensors with Unicorn Recorder software that is connected to the amplifier while recording is run. The result of the experiment also explained in terms of the mean value and standard deviation of the EEG bands for each subject and condition. The results of the study conclude that the IQ level of an individual is affected by the Beta band of the EEG signals. Meanwhile, Alpha band of the EEG signals is more dominant in the determination of EQ level of an individual. When Alpha band is higher than Beta band, it shows that the subject is dominant to an EQ dominant person. If Beta band is higher than Alpha band, then IQ is the dominant quotient for the subject. The highest k-NN classification accuracy is obtained at 80:20 classification with 81.84% accuracy using Mean features and 79.53% accuracy using Standard Deviaton features. This study also included the development of Graphical User Interface (GUI) in MATLAB. The GUI is used for the classification of the chosen EEG features. Theta, Alpha, and Beta power band are observed from the EEG signals to identify brain activity. In addition, IQ and EQ analyzer is constructed using Arduino microcontroller once the analysis of the EEG signals are done through GUI.
format Article
author Afiqah, Norsepri
Norizam, Sulaiman
Mahfuzah, Mustafa
Hasan, Md Mahmudul
Siti Armiza, Mohd Aris
author_facet Afiqah, Norsepri
Norizam, Sulaiman
Mahfuzah, Mustafa
Hasan, Md Mahmudul
Siti Armiza, Mohd Aris
author_sort Afiqah, Norsepri
title A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals
title_short A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals
title_full A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals
title_fullStr A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals
title_full_unstemmed A study of engineering student IQ and EQ based on analyzing of electroencephalogram (EEG) signals
title_sort study of engineering student iq and eq based on analyzing of electroencephalogram (eeg) signals
publisher Penerbit UMP
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/40082/1/A%20Study%20of%20Engineering%20Student%20IQ%20and%20EQ.pdf
http://umpir.ump.edu.my/id/eprint/40082/
https://doi.org/10.15282/mekatronika.v5i2.9853
https://doi.org/10.15282/mekatronika.v5i2.9853
_version_ 1822924095384190976
score 13.23243

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