EEG-Based Aesthetics Preference Measurement with 3D Stimuli using Wavelet Transform

Lin Hou Chew, and Jason Teo, and James Mountstephens, (2015) EEG-Based Aesthetics Preference Measurement with 3D Stimuli using Wavelet Transform. ARPN Journal of Engineering and Applied Sciences, 10 (22). ISSN 1819-6608

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Abstract

This study investigates on aesthetics preference measurement of human using electroencephalogram (EEG) for virtual motion 3D shapes. The 3D shapes are generated using the Gielis superformula in bracelet-like shapes. EEG signals were collected by using a wireless medical grade EEG device, B-Alert X10 from Advance Brain Monitoring. Wavelet transforms were used to decompose the signals into 5 different bands, alpha, beta, gamma, delta and theta. Linear Discriminant analysis (LDA) and K-Nearest Neighbor (KNN) were used as classifiers to train and test different combinations of the features. Classification accuracy of up to 82.14% could be obtained using KNN with entropy of beta, gamma, delta and theta rhythms as features from channels Fz, POz and P4.

Item Type: Article
Uncontrolled Keywords: aesthetics preference, electroencephalogram, brain computer interface, wavelet transform, 3-Dimensional design, K-nearest neighbor, linear discriminant analysis.
Subjects: B Philosophy. Psychology. Religion > BH Aesthetics
Divisions: FACULTY > Faculty of Computing and Informatics
Depositing User: MR OTHMAN HJ RAWI
Date Deposited: 15 Mar 2019 07:24
Last Modified: 15 Mar 2019 07:24
URI: http://eprints.ums.edu.my/id/eprint/21646

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