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- W2386272035 abstract "In order to label the electroencephalogram(EEG) under different imagery task in brain-computer inerface(BCI) technology,a practical classification method was put forward which was based on theory of event-related EEG desychronization/synchronization and support-vector machine(SVM) algorithm.In the algorithm,firstly a filter was used to filter the EEG to obtain the frequency band which was sensitive to imagery task,then the mean value was removed from the EEG to minimize the incidental error caused by it.Finally the field strength characteristics related to ERD/ERS were extracted as a vector and the vector was used by SVM to recognize the pattern of the EEG.The results show that this approach provides an effective way for the application of the brain-computer interface." @default.
- W2386272035 created "2016-06-24" @default.
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- W2386272035 date "2007-01-01" @default.
- W2386272035 modified "2023-09-23" @default.
- W2386272035 title "An Algorithm Research of EEG Classification on Motor Imagery" @default.
- W2386272035 hasPublicationYear "2007" @default.
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