A repeated bisection CSP feature extraction algorithm of four-class motor imagery EEG

Shu Hua Zheng; Chen Yan; Xiang Zhou Wang

doi:10.15918/j.tbit1001-0645.2016.08.013

A repeated bisection CSP feature extraction algorithm of four-class motor imagery EEG

Shu Hua Zheng, Chen Yan, Xiang Zhou Wang^*

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

In this paper, based on analysis of the phenomenon of ERD/ERS in brain-computer interface (BCI), an improved repeated bisection common spatial pattern (RB-CSP) algorithm was presented to extract the features of four-class motor imagery EEG and the support vector machine (SVM) was used to classify. The experimental results show that, the proposed algorithm can reduce time consumption and complexity, can produce high classification accuracy, compared with OVR-CSP of the CSP traditional extensions. The proposed algorithm provides a new solution to real-time BCI systems.

Original language	English
Pages (from-to)	844-850
Number of pages	7
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	36
Issue number	8
DOIs	https://doi.org/10.15918/j.tbit1001-0645.2016.08.013
Publication status	Published - 1 Aug 2016

Keywords

Brain computer interface (BCI)
Feature extraction
Four-class motor imagery
Repeated bisection common spatial pattern (RB-CSP) algorithm

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10.15918/j.tbit1001-0645.2016.08.013

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abstract = "In this paper, based on analysis of the phenomenon of ERD/ERS in brain-computer interface (BCI), an improved repeated bisection common spatial pattern (RB-CSP) algorithm was presented to extract the features of four-class motor imagery EEG and the support vector machine (SVM) was used to classify. The experimental results show that, the proposed algorithm can reduce time consumption and complexity, can produce high classification accuracy, compared with OVR-CSP of the CSP traditional extensions. The proposed algorithm provides a new solution to real-time BCI systems.",

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AU - Wang, Xiang Zhou

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N2 - In this paper, based on analysis of the phenomenon of ERD/ERS in brain-computer interface (BCI), an improved repeated bisection common spatial pattern (RB-CSP) algorithm was presented to extract the features of four-class motor imagery EEG and the support vector machine (SVM) was used to classify. The experimental results show that, the proposed algorithm can reduce time consumption and complexity, can produce high classification accuracy, compared with OVR-CSP of the CSP traditional extensions. The proposed algorithm provides a new solution to real-time BCI systems.

AB - In this paper, based on analysis of the phenomenon of ERD/ERS in brain-computer interface (BCI), an improved repeated bisection common spatial pattern (RB-CSP) algorithm was presented to extract the features of four-class motor imagery EEG and the support vector machine (SVM) was used to classify. The experimental results show that, the proposed algorithm can reduce time consumption and complexity, can produce high classification accuracy, compared with OVR-CSP of the CSP traditional extensions. The proposed algorithm provides a new solution to real-time BCI systems.

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KW - Feature extraction

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KW - Repeated bisection common spatial pattern (RB-CSP) algorithm

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A repeated bisection CSP feature extraction algorithm of four-class motor imagery EEG

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Keywords

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