Fugl-Meyer hand motor imagination recognition for brain-computer interfaces using only fNIRS
文献类型：期刊论文
| 作者 | Li, Chenguang1,2 ; Yang, Hongjun2; Cheng, Long1,2
|
| 刊名 | COMPLEX & INTELLIGENT SYSTEMS
 |
| 出版日期 | 2021-01-11 |
| 页码 | 11 |
| 关键词 | Brain-computer interface Functional near-infrared spectroscopy (fNIRS) Motor imagery Classification Empirical mode decomposition |
| ISSN号 | 2199-4536 |
| DOI | 10.1007/s40747-020-00266-w |
| 通讯作者 | Cheng, Long(long.cheng@ia.ac.cn) |
| 英文摘要 | 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. |
| WOS关键词 | IMAGERY |
| 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] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000607054600003 |
| 出版者 | SPRINGER HEIDELBERG |
| 资助机构 | National Natural Science Foundation of China ; Beijing Municipal Natural Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/42587]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 通讯作者 | Cheng, Long |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Control & Management Complex Syst, Beijing 100190, Peoples R China |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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