The design of multi-task simulation manipulator based on motor imagery EEG

Yuhang Ye, Chenguang Yang, Xinyang Li, Zhaojie Ju, Zhijun Li

Abstract: In this paper, a mind controlled multi-task manipulator based on motor imagery electroencephalogram (EEG) is proposed. Describe the system function first: In the case of only two types of control signal, the implementation of multi-task Manipulator relies on a toggle-confirmation mode of operation: the task is switched when imagining the left-hand movement, and the task is confirmed when the right-hand movement is imagined. In the BCI system, common spatial pattern (CSP) is used for feature extraction, mutual information for feature selection, and linear discriminant analysis (LDA) for pattern classification. The EEG signal is processed and classified into two categories, imagery of left-hand and right-hand movement. In this way, we can achieve the multi-task control of the manipulator under the premise of ensuring the accuracy of EEG recognition.