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Robot-Assisted Rehabilitation System Based on SSVEP Brain-Computer Interface for Upper Extremity
Chu YQ(褚亚奇)1,2,3; Zhao XG(赵新刚)1,2; Zou YJ(邹宜君)1,2,3; Xu WL(徐卫良)1,4; Zhao YW(赵忆文)1,2
Department机器人学研究室
Conference Name2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)
Conference DateDecember 12-15, 2018
Conference PlaceKuala Lumpur, Malaysia
Source PublicationProceedings of the 2018 IEEE International Conference on Robotics and Biomimetics
PublisherIEEE
Publication PlaceNew York
2018
Pages1058-1063
Indexed ByEI ; CPCI(ISTP)
EI Accession number20191506772482
WOS IDWOS:000468772200169
Contribution Rank1
ISBN978-1-7281-0376-1
AbstractTraditional rehabilitation therapies have limited effect on the motor recovery for a tetraplegia patient. Brain-computer interface (BCI) systems allow patients to send commands or intents to control external devices without depending on the normal way of peripheral nerves and muscles. And hence it can provide an alternative control and communication method with a potential to replace, restore, even reinforce lost movement ability for individuals with neurological damages. In the study, we proposed a robot-assisted rehabilitation system for upper extremity based on non-invasive electroencephalogram (EEG) BCI, which enables the injured upper extremity to achieve motor function. Six participants conducted three speed modes of movement with a BCI-controlled robot. The steady-state visual evoked potentials (SSVEPs) was adopted to establish the BCI system. Experimental results of the healthy participants were analyzed to indicate the feasibility of a BCI-driven robot-assisted rehabilitation system, with an average accuracy of about 80 %. This study gives a preliminary evidence that the integrated robot-assisted rehabilitation system combined with SSVEP-based BCI will make future rehabilitation therapy more effective.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/24659
Collection机器人学研究室
Corresponding AuthorZhao XG(赵新刚)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation (SIA), Chinese Academy of Sciences (CAS), China
2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences (CAS), Shenyang, Liaoning 110016, China
3.University of Chinese Academy of Sciences (UCAS), Beijing, China
4.Department of Mechanical Engineering, University of Auckland, Auckland 1142, New Zealand
Recommended Citation
GB/T 7714
Chu YQ,Zhao XG,Zou YJ,et al. Robot-Assisted Rehabilitation System Based on SSVEP Brain-Computer Interface for Upper Extremity[C]. New York:IEEE,2018:1058-1063.
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