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Emotional profiling through supervised machine learning of interrupted EEG interpolation

Yaacob, Hamwira Sakti and Omar, Hazim and Handayani, Dini and Hassan, Raini (2019) Emotional profiling through supervised machine learning of interrupted EEG interpolation. International Journal of Advanced Computer Research, 9 (43). pp. 242-251. ISSN 2249-7277 E-ISSN 2277-7970

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Abstract

It has been reported that the construction of emotion profiling models using supervised machine learning involves data acquisition, signal pre-processing, feature extraction and classification. However, almost all papers do not address the issue of profiling emotion using supervised machine learning on the interrupted encephalogram (EEG) signals. Based on a preliminary study, emotion profiling on interrupted EEG signals produces low classification accuracy, using multilayer perceptron (MLP). Furthermore, lower emotion classification accuracy is produced from interrupted EEG signals with higher number of segments. Thus, the objective of this paper is to propose a technique and present the outcomes of handling interrupted EEG signals for emotion profiling. This is done by the suppression and interpolation of originally interrupted EEG signals at pre-process stage. As a result, emotion classification using MLP on interpolated data improves from 80.1% to 95%.

Item Type: Article (Journal)
Additional Information: 4870/75492
Uncontrolled Keywords: Interrupted EEG, Interpolation, Emotion classification, Power spectral density
Subjects: B Philosophy. Psychology. Religion > BF Psychology > BF511 Affection. Feeling. Emotion
T Technology > T Technology (General) > T55.4 Industrial engineering.Management engineering. > T58.5 Information technology
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Dr Hamwira Yaacob
Date Deposited: 11 Nov 2019 18:27
Last Modified: 11 Nov 2019 18:27
URI: http://irep.iium.edu.my/id/eprint/75492

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