Time-Distributed Attention Network for EEG-Based Motor Imagery Decoding From the Same Limb | |
Ma, Xuelin1,2,3; Qiu, Shuang1; He, Huiguang1,4,5 | |
发表期刊 | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING |
ISSN | 1534-4320 |
2022 | |
卷号 | 30页码:496-508 |
通讯作者 | He, Huiguang(huiguang.he@ia.ac.cn) |
摘要 | A brain-computer interface (BCI) based on motor imagery (MI) from the same limb can provide an intuitive control pathway but has received limited attention. It is still a challenge to classify multiple MI tasks from the same limb. The goal of this study is to propose a novel decoding method to classify the MI tasks of four joints of the same upper limb and the resting state. EEG signals were collected from 20 participants. A time-distributed attention network (TD-Atten) was proposed to adaptively assign different weights to different classes and frequency bands of the input multiband Common Spatial Pattern (CSP) features. The long short-term memory (LSTM) and dense layers were then used to learn sequential information from the reweight features and perform the classification. Our proposed method outperformed other baseline and deep learning-based methods and obtained the accuracies of 46.8% in the 5-class scenario and 53.4% in the 4-class scenario. The visualization results of attention weights indicated that the proposed framework can adaptively pay attention to alpha-band related features in MI tasks, which was consistent with the analysis of brain activation patterns. These results demonstrated the feasibility and interpretability of the attention mechanism in MI decoding and the potential of this fine MI paradigm to be applied for the control of a robotic arm or a neural prosthesis. |
关键词 | Attention mechanism electroencephalography (EEG) fine motor imagery same limb |
DOI | 10.1109/TNSRE.2022.3154369 |
关键词[WOS] | BRAIN-COMPUTER INTERFACE ; SINGLE-TRIAL EEG ; NEURAL-NETWORKS ; CLASSIFICATION ; REAL ; DYNAMICS ; MACHINE |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2018YFC2001302] ; National Natural Science Foundation of China[U21A20388] ; National Natural Science Foundation of China[81701785] ; National Natural Science Foundation of China[61976209] ; National Natural Science Foundation of China[62020106015] ; CAS International Collaboration Key Project[173211KYSB20190024] ; Strategic Priority Research Program of CAS[XDB32040000] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; CAS International Collaboration Key Project ; Strategic Priority Research Program of CAS |
WOS研究方向 | Engineering ; Rehabilitation |
WOS类目 | Engineering, Biomedical ; Rehabilitation |
WOS记录号 | WOS:000767839400002 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 脑机接口 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/47985 |
专题 | 类脑智能研究中心_神经计算与脑机交互 |
通讯作者 | He, Huiguang |
作者单位 | 1.Chinese Acad Sci CASIA, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing 100190, Peoples R China 2.JD Com, Beijing 100176, Peoples R China 3.Univ Chinese Acad Sci UCAS, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100864, Peoples R China 5.Univ Chinese Acad Sci UCAS, Beijing 100049, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Ma, Xuelin,Qiu, Shuang,He, Huiguang. Time-Distributed Attention Network for EEG-Based Motor Imagery Decoding From the Same Limb[J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,2022,30:496-508. |
APA | Ma, Xuelin,Qiu, Shuang,&He, Huiguang.(2022).Time-Distributed Attention Network for EEG-Based Motor Imagery Decoding From the Same Limb.IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,30,496-508. |
MLA | Ma, Xuelin,et al."Time-Distributed Attention Network for EEG-Based Motor Imagery Decoding From the Same Limb".IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 30(2022):496-508. |
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