NDLI: A feasibility study of non-invasive motor-imagery BCI-based robotic rehabilitation for Stroke patients

Content Provider	IEEE Xplore Digital Library
Author	Chuanchu Wang Kok Soon Phua Kai Keng Ang Cuntai Guan Haihong Zhang Rongsheng Lin Chua, K.S.G. Beng Ti Ang Kuah, C.W.K.
Copyright Year	2009
Description	Author affiliation: Institute for Infocomm Research, A*STAR, Singapore (Chuanchu Wang; Kok Soon Phua; Kai Keng Ang; Cuntai Guan; Haihong Zhang; Rongsheng Lin) \|\| Tan Tock Seng Hospital Rehabilitation Centre, Singapore (Chua, K.S.G.; Kuah, C.W.K.) \|\| National Neuroscience Institute, Singapore (Beng Ti Ang)
Abstract	This paper describes an initial study of non-invasive electroencephalograph (EEG)-based Brain Computer Interface (BCI) application on Stroke patients. The purpose of this study is to combine BCI and robotic arm for after-stroke rehabilitation exercises. A clinically-proven MANUS robotic rehabilitation shell is integrated with the NeuroComm BCI platform, whereby the robotic control mechanism is complemented by the motor imagery of the patient. 8 hemiparetic stroke patients with varying degrees of paralysis on the unilateral upper extremity are recruited for this study. The results show that most BCI-naïve hemiparetic stroke patients are capable of operating the BCI effectively, hence motivates further clinical studies on the extent of how BCI-based robotic rehabilitation are comparable with the control group that uses only robotic rehabilitation.
Starting Page	271
Ending Page	274
File Size	870887
Page Count	4
File Format	PDF
ISBN	9781424420728
DOI	10.1109/NER.2009.5109285
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-29
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	non-invasive BCI Robot control Neural engineering Application software Recruitment Leg stroke rehabilitation Neuroscience Hospitals robot-aided rehabilitation Rehabilitation robotics Extremities Brain computer interfaces
Content Type	Text
Resource Type	Article

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