DOI: 10.14704/nq.2018.16.6.1584

Brain-Computer Interface Data Classification Based on Support Vector Machine

Jun Zheng, Yujie Zhou

Abstract


Brain-computer interface is a kind of communication system which establishes information output pathways that is independent from the common brain information output pathways between the brain and the outside world. P300 potential is an ordinary electroencephalogram (EEG) used to construct the brain-computer interface systems. In this paper, P300 EEG signals are preprocessed to extract the features, at last Support Vector Machine (SVM) is used to classify and recognize the EEG signals, and the brain-computer interface data classification research is successfully implemented.

Keywords


Brain-computer Interface, P300, SVM, Classification

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References


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