Classification Algorithm for Electroencephalogram-based Motor Imagery Using Hybrid Neural Network with Spatio-temporal Convolution and Multi-head Attention Mechanism-Reference-Cited by-同舟云学术

Classification Algorithm for Electroencephalogram-based Motor Imagery Using Hybrid Neural Network with Spatio-temporal Convolution and Multi-head Attention Mechanism

Published:2023-09 Issue: Volume:527 Page:64-73
ISSN:0306-4522
Container-title:Neuroscience
language:en
Short-container-title:Neuroscience

Author:

Shi Xingbin^ORCID,Li Baojiang^ORCID,Wang Wenlong,Qin Yuxin,Wang Haiyan,Wang Xichao

Publisher

Elsevier BV

Subject

General Neuroscience

Reference46 articles.

1. Feature extraction of four-class motor imagery EEG signals based on functional brain network;Ai;J Neural Eng,2019

2. Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: a review;Altaheri;Neural Comput Appl,2021

3. Physics-informed attention temporal convolutional network for EEG-based motor imagery classification;Altaheri;IEEE Trans Ind Inf,2022

4. Dynamic convolution with multilevel attention for EEG-based motor imagery decoding;Altaheri;IEEE Internet Things J,2023

5. Attention-inception and long-short-term memory-based electroencephalography classification for motor imagery tasks in rehabilitation;Amin;IEEE Trans Ind Inf,2021

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