Parallel spatial-temporal self-attention CNN-based motor imagery classification for BCI

Motor imagery (MI) electroencephalography (EEG) classification is an important part of the brain-computer interface (BCI), allowing people with mobility problems to communicate with the outside world via assistive devices. However, EEG decoding is a challenging task because of its complexity, dynami...

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Bibliographic Details
Main Authors: Liu, Xiuling, Shen, Yonglong, Liu, Jing, Yang, Jianli, Xiong, Peng, Lin, Feng
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2021
Subjects:
EEG
Online Access:https://hdl.handle.net/10356/146014
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Institution: Nanyang Technological University
Language: English

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