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K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning

This paper proposes a method to detect situational interest in classroom learning using k-means algorithms. The developed algorithm in this paper had been tested on features from ten students who experienced mathematics learning in a classroom. The subjects were given 21Â min of Laplace lecture pres...

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Main Authors: Othman, E.S., Faye, I., Babiker, A., Hussaan, A.M.
Format: Conference or Workshop Item
Published: Springer Science and Business Media B.V. 2021
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123276466&doi=10.1007%2f978-981-16-4513-6_47&partnerID=40&md5=3f4c92f3574e9582beb6ff78b4a0ec4d
http://eprints.utp.edu.my/29304/
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spelling my.utp.eprints.293042022-03-25T01:33:34Z K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning Othman, E.S. Faye, I. Babiker, A. Hussaan, A.M. This paper proposes a method to detect situational interest in classroom learning using k-means algorithms. The developed algorithm in this paper had been tested on features from ten students who experienced mathematics learning in a classroom. The subjects were given 21 min of Laplace lecture presentation with some interesting elements introduced. Electroencephalogram (EEG) signal was preprocessed and decomposed using Fast Fourier Transform. The mean power for each sub-frequency band was served as input to the k-means algorithm. Results showed that EEG features can be successfully clustered in the alpha frequency band at the frontal region when visual-auditory stimuli are introduced to the subjects. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Springer Science and Business Media B.V. 2021 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123276466&doi=10.1007%2f978-981-16-4513-6_47&partnerID=40&md5=3f4c92f3574e9582beb6ff78b4a0ec4d Othman, E.S. and Faye, I. and Babiker, A. and Hussaan, A.M. (2021) K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning. In: UNSPECIFIED. http://eprints.utp.edu.my/29304/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description This paper proposes a method to detect situational interest in classroom learning using k-means algorithms. The developed algorithm in this paper had been tested on features from ten students who experienced mathematics learning in a classroom. The subjects were given 21 min of Laplace lecture presentation with some interesting elements introduced. Electroencephalogram (EEG) signal was preprocessed and decomposed using Fast Fourier Transform. The mean power for each sub-frequency band was served as input to the k-means algorithm. Results showed that EEG features can be successfully clustered in the alpha frequency band at the frontal region when visual-auditory stimuli are introduced to the subjects. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
format Conference or Workshop Item
author Othman, E.S.
Faye, I.
Babiker, A.
Hussaan, A.M.
spellingShingle Othman, E.S.
Faye, I.
Babiker, A.
Hussaan, A.M.
K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
author_facet Othman, E.S.
Faye, I.
Babiker, A.
Hussaan, A.M.
author_sort Othman, E.S.
title K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
title_short K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
title_full K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
title_fullStr K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
title_full_unstemmed K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
title_sort k-means clustering analysis for eeg features of situational interest detection in classroom learning
publisher Springer Science and Business Media B.V.
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123276466&doi=10.1007%2f978-981-16-4513-6_47&partnerID=40&md5=3f4c92f3574e9582beb6ff78b4a0ec4d
http://eprints.utp.edu.my/29304/
_version_ 1738656946856132608
score 13.160551

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