Impact of VR Educational Games on Users: A Classification Algorithm Based on EEG Signal Feature Extraction

DOI

10.2991/978-94-6463-815-8_70How to use a DOI?

Keywords

Virtual reality games; Attention; Ensemble empirical mode decomposition; Support vector machines

Abstract

Attention has a significant impact on cognitive abilities including learning and deciding. Under the fast growth of internet technology, virtual reality has also greatly progressed. Exploring the impact of virtual reality games on attention is of great importance, but quantitative analysis on the influence of virtual games on attention is inadequate. To address this issue, a method based on support vector machines is invented to judge and classify electroencephalography signals. Firstly, a method based on wavelet thresholding and ensemble empirical mode decomposition is proposed to address the problem of difficult extraction and processing of electroencephalography signals. This method can preprocess the real-time electroencephalography signals collected from users in different attention states, and then classify the signals using an improved support vector machines. Experiment outcomes told that when the training set size is 500, the root mean square error values of the wavelet thresholding method, ensemble empirical mode decomposition, and hybrid algorithm are 0.25, 0.19, and 0.16. The values of the hybrid algorithm for the alpha, beta, theta, and delta frequency bands are 0.09, 0.15, 0.19, and 0.11, respectively. When the dataset size is 800, the root mean square error values of the convolutional neural network model, support vector machines model, and improved support vector machines model are 0.19, 0.16, and 0.13, respectively. The research results indicate that the proposed hybrid denoising algorithm and improved support vector machines model have good model performance, providing theoretical support for attention training and testing in fields such as psychology and education.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ying Zhao
AU  - Guocheng Wei
PY  - 2025
DA  - 2025/08/13
TI  - Impact of VR Educational Games on Users: A Classification Algorithm Based on EEG Signal Feature Extraction
BT  - Proceedings of the 2025 4th International Conference on Art Design and Digital Technology (ADDT 2025)
PB  - Atlantis Press
SP  - 632
EP  - 650
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-815-8_70
DO  - 10.2991/978-94-6463-815-8_70
ID  - Zhao2025
ER  -