Affiliated with RCfalse
Status即將出版Forthcoming
SSVEP-Based Brain Computer Interface Controlled Soft Robotic Glove for Post-Stroke Hand Function Rehabilitation
Guo, Ning1,2; Wang, Xiaojun1,2; Duanmu, Dehao1,2; Huang, Xin3; Li, Xiaodong1,2; Fan, Yunli1,2; Li, Hailan3; Liu, Yongquan3; Yeung, Eric Hiu Kwong3; To, Michael Kai Tsun4; Gu, Jianxiong5; Wan, Feng6,7; Hu, Yong1,2
2022
Source PublicationIEEE Transactions on Neural Systems and Rehabilitation Engineering
ISSN1534-4320
Volume30Pages:1737-1744
Abstract

Soft robotic glove with brain computer interfaces (BCI) control has been used for post-stroke hand function rehabilitation. Motor imagery (MI) based BCI with robotic aided devices has been demonstrated as an effective neural rehabilitation tool to improve post-stroke hand function. It is necessary for a user of MI-BCI to receive a long time training, while the user usually suffers unsuccessful and unsatisfying results in the beginning. To propose another non-invasive BCI paradigm rather than MI-BCI, steady-state visually evoked potentials (SSVEP) based BCI was proposed as user intension detection to trigger the soft robotic glove for post-stroke hand function rehabilitation. Thirty post-stroke patients with impaired hand function were randomly and equally divided into three groups to receive conventional, robotic, and BCI-robotic therapy in this randomized control trial (RCT). Clinical assessment of Fugl-Meyer Motor Assessment of Upper Limb (FMA-UL), Wolf Motor Function Test (WMFT) and Modified Ashworth Scale (MAS) were performed at pre-training, post-training and three months follow-up. In comparing to other groups, The BCI-robotic group showed significant improvement after training in FMA full score (10.05 ± 8.03, p = 0.001), FMA shoulder/elbow (6.2 ± 5.94, p = 0.0004) and FMA wrist/hand (4.3 ± 2.83, p = 0.007), and WMFT (5.1 ± 5.53, p = 0.037). The improvement of FMA was significantly correlated with BCI accuracy (r = 0.714, p = 0.032). Recovery of hand function after rehabilitation of SSVEP-BCI controlled soft robotic glove showed better result than solely robotic glove rehabilitation, equivalent efficacy as results from previous reported MI-BCI robotic hand rehabilitation. It proved the feasibility of SSVEP-BCI controlled soft robotic glove in post-stroke hand function rehabilitation.

KeywordBrain Computer Interfaces (Bci) Hand Rehabilitation Post Stroke Soft Robotic Glove Steady-state Visually Evoked Potentials (Ssvep)
DOI10.1109/TNSRE.2022.3185262
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering ; Rehabilitation
WOS SubjectEngineering, Biomedical ; Rehabilitation
WOS IDWOS:000821498100001
Scopus ID2-s2.0-85133731842
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Affiliation1.Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, 518172, China
2.The University of Hong Kong, Department of Orthopaedics and Traumatology, Hong Kong, Hong Kong
3.Shenzhen Hospital, the University of Hong Kong, Physiotherapy and Occupational Therapy Divisions, Department of Rehabilitation Medicine, Shenzhen, 518172, China
4.The University of Hong Kong, Shenzhen Hospital, Department of Orthopaedics and Traumatology, Shenzhen, 518172, China
5.Affiliated Hospital of Guangdong Medical University, Department of Rehabilitation, Guangdong, 524001, China
6.University of Macau, Avenida da Universidade, Faculty of Science and Technology, Department of Electrical and Computer Engineering, 519020, Macao
7.Institute of Collaborative Innovation, University of Macau, Avenida da Universidade, Centre for Cognitive and Brain Sciences, 519020, Macao
Recommended Citation
GB/T 7714
Guo, Ning,Wang, Xiaojun,Duanmu, Dehao,et al. SSVEP-Based Brain Computer Interface Controlled Soft Robotic Glove for Post-Stroke Hand Function Rehabilitation[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering,2022,30:1737-1744.
APA Guo, Ning,Wang, Xiaojun,Duanmu, Dehao,Huang, Xin,Li, Xiaodong,Fan, Yunli,Li, Hailan,Liu, Yongquan,Yeung, Eric Hiu Kwong,To, Michael Kai Tsun,Gu, Jianxiong,Wan, Feng,&Hu, Yong.(2022).SSVEP-Based Brain Computer Interface Controlled Soft Robotic Glove for Post-Stroke Hand Function Rehabilitation.IEEE Transactions on Neural Systems and Rehabilitation Engineering,30,1737-1744.
MLA Guo, Ning,et al."SSVEP-Based Brain Computer Interface Controlled Soft Robotic Glove for Post-Stroke Hand Function Rehabilitation".IEEE Transactions on Neural Systems and Rehabilitation Engineering 30(2022):1737-1744.
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