Multi-tasks Channel Selection Algorithmic Modeling Based on SVM-RFE

doi:10.16182/j.issn1004731x.joss.201812002

Abstract

Abstract: Channel selection is used to locate the mental task related brain area in the brain computer interface systems. In the previous studies, the channels were selected based on the data recoded from the multi-mental tasks. However, the different mental tasks are corresponding to the different brain area. If one same brain area is selected for different mental tasks, the features of one mental task would be noises of another mental task. In this paper, a new method was presented to solve this problem based on the data of motor imagery tasks. The SVM-RFE method was used to select the channels for each motor imagery task based on recall rate. The result showed that the proposed channel selection method was superior to the traditional method in classification accuracy.

Key words: brain-computer interface, motor imagery, SVM-RFE, multi-tasks

CLC Number:

TP273

Feng Jiankui, Jin Jing, Wang Bei, Niu Yugang, Wang Xingyu. Multi-tasks Channel Selection Algorithmic Modeling Based on SVM-RFE[J]. Journal of System Simulation, 2018, 30(12): 4506-4512.

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