Euler common spatial patterns for EEG classification
文献类型:期刊论文
作者 | Sun, Jing1,2; Wei, Mengting3; Luo, Ning4; Li, Zhanli5; Wang, Haixian1,2 |
刊名 | MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING |
出版日期 | 2022 |
页码 | 15 |
ISSN号 | 0140-0118 |
关键词 | Euler representation Common spatial patterns (CSP) Brain-computer interface (BCI) Electroencephalogram (EEG) Feature extraction |
DOI | 10.1007/s11517-021-02488-7 |
通讯作者 | Wang, Haixian(hxwang@seu.edu.cn) |
产权排序 | 3 |
文献子类 | 综述 |
英文摘要 | The technique of common spatial patterns (CSP) is a widely used method in the field of feature extraction of electroencephalogram (EEG) signals. Motivated by the fact that a cosine distance can enlarge the distance between samples of different classes, we propose the Euler CSP (e-CSP) for the feature extraction of EEG signals, and it is then used for EEG classification. The e-CSP is essentially the conventional CSP with the Euler representation. It includes the following two stages: each sample value is first mapped into a complex space by using the Euler representation, and then the conventional CSP is performed in the Euler space. Thus, the e-CSP is equivalent to applying the Euler representation as a kernel function to the input of the CSP. It is computationally as straightforward as the CSP. However, it extracts more discriminative features from the EEG signals. Extensive experimental results illustrate the discrimination ability of the e-CSP. |
收录类别 | EI |
WOS关键词 | BRAIN-COMPUTER INTERFACES ; BCI ; P300 |
资助项目 | National Natural Science Foundation of China[62176054] ; University Synergy Innovation Program of Anhui Province[GXXT-2020-015] |
WOS研究方向 | Computer Science ; Engineering ; Mathematical & Computational Biology ; Medical Informatics |
语种 | 英语 |
出版者 | SPRINGER HEIDELBERG |
WOS记录号 | WOS:000745355900001 |
资助机构 | National Natural Science Foundation of China ; University Synergy Innovation Program of Anhui Province |
源URL | [http://ir.psych.ac.cn/handle/311026/41823] |
专题 | 中国科学院心理研究所 |
作者单位 | 1.Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Jiangsu, Nanjing; 210096, China 2.Institute of Artificial Intelligence of Hefei Comprehensive National Science Center, Anhui, Hefei; 230094, China 3.Institute of Psychology, Chinese Academy of Sciences, Beijing; 100101, China 4.Institute of Software, Chinese Academy of Sciences, Beijing; 100190, China 5.College of Computer Science and Technology, Xi’an University of Science and Technology, Shanxi, Xi’an; 710054, China |
推荐引用方式 GB/T 7714 | Sun, Jing,Wei, Mengting,Luo, Ning,et al. Euler common spatial patterns for EEG classification[J]. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING,2022:15. |
APA | Sun, Jing,Wei, Mengting,Luo, Ning,Li, Zhanli,&Wang, Haixian.(2022).Euler common spatial patterns for EEG classification.MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING,15. |
MLA | Sun, Jing,et al."Euler common spatial patterns for EEG classification".MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2022):15. |
入库方式: OAI收割
来源:心理研究所
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