2-D GCANet Applied to Denoise 1-D EEG Signals in Online Remote Teaching Scenarios

被引：0

作者：

Huang, Ting-Qing ^{[1
]}

Wang, Chuan-Sheng ^{[2
]}

Chen, Zhao-Qi ^{[3
]}

Zhang, Fu-Quan ^{[1
,4
,5
,6
]}

Meng, Xiang-Long ^{[7
]}

Grau, Antoni ^{[2
]}

Chen, Yang ^{[8
]}

Huang, Jing-Wei ^{[3
]}

机构：

[1] College of Computer and Control Engineering, Minjiang University, Fuzhou University Town, No. 200 Xiyuangong Road, Fuzhou, China

[2] Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia, Barcelona, Spain

[3] College of Computer and Big Data Fuzhou University, Fuzhou University Town, No. 2 Wulong Jiangbei Avenue, Fuzhou, China

[4] Digital Media Art, Key Laboratory of Sichuan Province Sichuan Conservatory of Music, No. 2 Wannianchang Street, Chenghua District, Sichuan Province, Chengdu City, China

[5] Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University, Fuzhou University Town, NO. 200 Xiyuangong Road, Fuzhou, China

[6] Engineering Research Center for ICH Digitalization and Multi-source Information Fusion(Fujian Polytechnic Normal University), Fujian Province University, No. 599 Quanxiu Road, Juyuanzhou Ecological Civilization District, Fujian Province, Fuzhou City, China

[7] College of Electronic Engineering Shandong University of Science and Technology, No. 579 Qianwangang Road, Huangdao District, Qingdao, China

[8] School of Mechanical and Automotive Engineering Fujian University of Technology, No. 33, Xuefu South Road, University New District, Fujian Province, Fuzhou City, China

来源：

Journal of Network Intelligence | 2023年 / 8卷 / 04期

关键词：

Artifact removal - De-Noise - De-noising - Deep learning - EEG artifact removal - EEG denoising - EEG signals - Neural-networks - Remote teaching - Student engagement;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

页码：1289 / 1302

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