Eegformer: a transformer-based brain activity classification method using eeg signal

HIGHLIGHTS

• who: Zhijiang Wan from the Renmin Hospital of Wuhan University, China have published the research: EEGformer: A transformer-based brain activity classification method using EEG signal, in the Journal: (JOURNAL)
• what: The authors propose a transformer-based EEG analysis model known as the EEGformer (Vaswani et_al, 2017) to capture the EEG characteristics in the SSVEPs-based BCI task.
• how: Assuming the raw data is collected from C EEG channels there are M depth-wise convolutional filters for generating M feature maps. For the emotion recognition task the authors used arousal valence and dominance . . .
  

   

  

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