A Model Combining Multi Branch Spectral-Temporal CNN, Efficient Channel Attention, and LightGBM for MI-BCI Classification-Reference-Cited by-同舟云学术

A Model Combining Multi Branch Spectral-Temporal CNN, Efficient Channel Attention, and LightGBM for MI-BCI Classification

Published:2023 Issue: Volume:31 Page:1311-1320
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Jia Hai¹^ORCID,Yu Shiqi¹,Yin Shunjie¹,Liu Lanxin¹,Yi Chanlin²^ORCID,Xue Kaiqing³,Li Fali²^ORCID,Yao Dezhong²^ORCID,Xu Peng²^ORCID,Zhang Tao¹^ORCID

Affiliation:

1. Mental Health Education Center and School of Science, Xihua University, Chengdu, China

2. MOE Key Laboratory for Neuroinformation, Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China

3. School of Computer and Software Engineering, Xihua University, Chengdu, China

Funder

National Natural Science Foundation of China

Project of Science and Technology Department of Sichuan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/10031624/10042017.pdf?arnumber=10042017

Reference63 articles.

1. On the use of convolutional neural networks and augmented CSP features for multi-class motor imagery of EEG signals classification;yang;Proc 37th Annu Int Conf IEEE Eng Med Biol Soc (EMBC),2015

2. A novel hybrid deep learning scheme for four-class motor imagery classification

3. Filter Bank Common Spatial Pattern Algorithm on BCI Competition IV Datasets 2a and 2b

4. Squeeze-and-Excitation Networks

5. Comparative Analysis of Spectral Approaches to Feature Extraction for EEG-Based Motor Imagery Classification

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