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A2FWPO: Anti-aliasing Filter Based on Whale Parameter Optimization Method for Feature Extraction and Recognition of Dance Motor Imagery EEG

Tianliang Huang¹, Ziyue Luo¹ and Yin Lyu²

1. School of Art, Hunan University of Information Technology
   Maotang Industrial Park, Changsha Economic and Technological Development Zone (410151) China
   tlhuang2023@163.com luoziyue77@163.com
2. College of Music, Huaiyin Normal University
   Huai'an, China
   8201711037@hytc.edu.cn

Abstract

The classification accuracy of EEG signals based on traditional machine learning methods is low. Therefore, this paper proposes a new model for the feature extraction and recognition of dance motor imagery EEG, which makes full use of the advantage of anti-aliasing filter based on whale parameter optimization method. The anti-aliasing filter is used for preprocessing, and the filtered signal is extracted by two-dimensional empirical wavelet transform. The extracted feature is input to the robust support matrix machine to complete pattern recognition. In pattern recognition process, an improved whale algorithm is used to dynamically adjust the optimal parameters of individual subjects. Experiments are carried out on two public data sets to verify that anti-aliasing filter-based preprocessing can improve signal feature discrimination. The improved whale algorithm can find the optimal parameters of robust support matrix machine classification for individuals. This presented method can improve the recognition rate of dance motion image. Compared with other advanced methods, the proposed method requires less samples and computing resources, and it is suitable for the practical application of brain-computer interface.

Key words

EEG signals classification, Dance motor imagery, Anti-aliasing filter, Whale parameter optimization, Two-dimensional empirical wavelet transform, Robust support matrix machine

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS221222033H

Publication information

Volume 20, Issue 4 (September 2023)
Year of Publication: 2023
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Huang, T., Luo, Z., Lyu, Y.: A2FWPO: Anti-aliasing Filter Based on Whale Parameter Optimization Method for Feature Extraction and Recognition of Dance Motor Imagery EEG. Computer Science and Information Systems, Vol. 20, No. 4. (2023), https://doi.org/10.2298/CSIS221222033H