Deep learning in eeg: advance of the last ten-year critical period

HIGHLIGHTS

• who: Ten-Year Critical Period et al. from the between channelsTo utilize comprehensive information from different data forms, Tian et_al [80] used three CNNs to, respectively, obtain features existing in the time, frequency, and time-frequency domain, and then utilized these features for seizure detection. By comparing with the methods that utilizing features from only one domain, the proposed method exhibited better performance. According to the study comparing among raw EEG signal, Fourier transform, wavelet transform, and empirical mode decomposition, raw signals and empirical mode decomposition were better than the others in distinguishing focal EEG from nonfocal . . .
  

   

  

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