Knowledge Commons of Institute of Automation,CAS
Fugl-Meyer hand motor imagination recognition for brain-computer interfaces using only fNIRS | |
Li, Chenguang1,2; Yang, Hongjun1; Cheng, Long1,2 | |
发表期刊 | COMPLEX & INTELLIGENT SYSTEMS |
ISSN | 2199-4536 |
2021-01-11 | |
页码 | 11 |
摘要 | As a relatively new physiological signal of brain, functional near-infrared spectroscopy (fNIRS) is being used more and more in brain-computer interface field, especially in the task of motor imagery. However, the classification accuracy based on this signal is relatively low. To improve the accuracy of classification, this paper proposes a new experimental paradigm and only uses fNIRS signals to complete the classification task of six subjects. Notably, the experiment is carried out in a non-laboratory environment, and movements of motion imagination are properly designed. And when the subjects are imagining the motions, they are also subvocalizing the movements to prevent distraction. Therefore, according to the motor area theory of the cerebral cortex, the positions of the fNIRS probes have been slightly adjusted compared with other methods. Next, the signals are classified by nine classification methods, and the different features and classification methods are compared. The results show that under this new experimental paradigm, the classification accuracy of 89.12% and 88.47% can be achieved using the support vector machine method and the random forest method, respectively, which shows that the paradigm is effective. Finally, by selecting five channels with the largest variance after empirical mode decomposition of the original signal, similar classification results can be achieved. |
关键词 | Brain-computer interface Functional near-infrared spectroscopy (fNIRS) Motor imagery Classification Empirical mode decomposition |
DOI | 10.1007/s40747-020-00266-w |
关键词[WOS] | IMAGERY |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[U1913209] ; National Natural Science Foundation of China[62025307] ; National Natural Science Foundation of China[61873268] ; Beijing Municipal Natural Science Foundation[JQ19020] |
项目资助者 | National Natural Science Foundation of China ; Beijing Municipal Natural Science Foundation |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000607054600003 |
出版者 | SPRINGER HEIDELBERG |
七大方向——子方向分类 | 脑机接口 |
国重实验室规划方向分类 | 智能能力评估 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/42588 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
通讯作者 | Cheng, Long |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Control & Management Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, 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 | Li, Chenguang,Yang, Hongjun,Cheng, Long. Fugl-Meyer hand motor imagination recognition for brain-computer interfaces using only fNIRS[J]. COMPLEX & INTELLIGENT SYSTEMS,2021:11. |
APA | Li, Chenguang,Yang, Hongjun,&Cheng, Long.(2021).Fugl-Meyer hand motor imagination recognition for brain-computer interfaces using only fNIRS.COMPLEX & INTELLIGENT SYSTEMS,11. |
MLA | Li, Chenguang,et al."Fugl-Meyer hand motor imagination recognition for brain-computer interfaces using only fNIRS".COMPLEX & INTELLIGENT SYSTEMS (2021):11. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Fugl-Meyer Hand Moto(1767KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论