Classification of EEG Signal by STFT-CNN Framework: Identification of Right-/left-hand Motor Imagination in BCI Systems
نویسندگان
چکیده
This paper described the relationship between EEG signals and MI in BCI system. EEG signals are used to classify the direction of motioninto two kinds: left and right. We extracted features from original EEG data using STFT and put them into CNN. The result showed that the framework of STFT-CNN had higher average test accuracy. Furthermore, the generations of motor imagery were analyzed, and the result showed that better classification results will appear in the middle stage with its classification accuracy reaching 92.8%.
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