The study of classification of motor imaginaries based on kurtosis of EEG

Authors:
Xiaopei Wu;Zhongfu Ye
Affiliations:
The Key Laboratory of Intelligent Computing & Signal Processing of MOE, Anhui University, Hefei, Anhui province, China and Department of Electronic Engineering and Information Science, USTC, H ...;Department of Electronic Engineering and Information Science, USTC, Hefei, Anhui province, China
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

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IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)

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Abstract

In this paper, the kurtosis-based method for the classification of mental activities is proposed. The EEG signals were recorded during imagination of left or right hand movement. The kurtosis of EEG and its dynamic properties with respect to time are analyzed. The experiment results show that the kurtosis can reflect the EEG pattern changes of different motor imageries. According to the analysis and experiment results, a kurtosis based classifier for the classification of left and right movement imagination is designed. This classifier can achieves near 90% correct rate. As the kurtosis is computationally less demanding and can also be estimated in on-line way, so the new method proposed in this paper has the practicability in the application of brain-computer interface.