The Classification Method of EEG Motor Imagery Based on INFO-LSSVM

Xinrong Wang, Abdelkader Nasreddine Belkacem, Penghai Li, Zufeng Zhang, Jun Liang, Dongdong Du, Chao Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution


For the current situation that the classification accuracy of EEG motor image data is not high in the BCI system, a vector weighted average algorithm optimization algorithm is proposed, and the optimized least squares support vector machine algorithm is proposed to classify the EEG motor image data. A motor imagination EEG experimental paradigm was designed and compared with the unoptimized LSSVM and three other typical classification methods on the same dataset. The experimental data were band-pass filtered by the fourth-order Butterworth filter of 0.5-30Hz, and the electrical interference was removed by independent component analysis. The HHT features obtained by empirical mode decomposition (EMD) and Hilbert Yellow transform (HHT) in the time-frequency domain were input into INFO-LSSVM for classification. Compared with dense feature fusion convolutional neural network (DFFN), Restricted Boltzmann machine optimized support vector Machine classifier (RBM-SVM) and public space pattern based artificial Neural network (CSP-ANN) classification algorithm, the highest classification accuracy of the proposed algorithm is 92.13%, and the average accuracy is 90.325%. It can be seen that compared with the existing algorithms with higher performance, the proposed algorithm effectively improves the classification accuracy and can better classify and identify EEG signals, which provides a new optimization idea for people's EEG signal classification.

Original languageEnglish
Title of host publicationProceedings of the 2022 11th International Conference on Computing and Pattern Recognition, ICCPR 2022
PublisherAssociation for Computing Machinery
Number of pages7
ISBN (Electronic)9781450397056
Publication statusPublished - Nov 17 2022
Event11th International Conference on Computing and Pattern Recognition, ICCPR 2022 - Virtual, Online, China
Duration: Nov 17 2022Nov 19 2022

Publication series

NameACM International Conference Proceeding Series


Conference11th International Conference on Computing and Pattern Recognition, ICCPR 2022
CityVirtual, Online


  • EEG signal classification
  • Least squares support vector machine
  • Motor imagery EEG
  • Weighted mean of vectors algorithm

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software


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