DocumentCode :
2964042
Title :
BCI-FES training system design and implementation for rehabilitation of stroke patients
Author :
Meng, Fei ; Tong, Kai-yu ; Chan, Suk-tak ; Wong, Wan-wa ; Lui, Ka-him ; Tang, Kwok-wing ; Gao, Xiaorong ; Gao, Shangkai
Author_Institution :
Dept. of Biomed. Eng., Tsinghua Univ., Beijing
fYear :
2008
fDate :
1-8 June 2008
Firstpage :
4103
Lastpage :
4106
Abstract :
A BCI-FES training platform has been designed for rehabilitation on chronic stroke patients to train their upper limb motor functions. The conventional functional electrical stimulation (FES) was driven by userspsila intention through EEG signals to move their wrist and hand. Such active participation was expected to be important for motor rehabilitation according to motor relearning theory. The common spatial pattern (CSP) algorithm was applied as one pre-processing step in brain-computer interface (BCI) module to search for the optimal spatial projection direction after brain reorganization. The pre- and post- clinical assessment was conducted to identify the possible functional improvement after the training. Two chronic stroke subjects attended this pilot study and the error rate of the BCI control was less than 20% after training of 10 sessions. This implementation showed the feasibility for stroke patients to accomplish the BCI triggered FES rehabilitation training.
Keywords :
brain-computer interfaces; electroencephalography; medical signal processing; patient rehabilitation; EEG signals motor relearning theory; brain reorganization; brain-computer interface; chronic stroke patients rehabilitation; common spatial pattern algorithm; functional electrical stimulation; optimal spatial projection direction; upper limb motor functions; Biomedical engineering; Biomedical imaging; Biomedical informatics; Brain computer interfaces; Electrodes; Electroencephalography; Feedback; Muscles; Neuromuscular stimulation; Wrist;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
ISSN :
1098-7576
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2008.4634388
Filename :
4634388
Link To Document :
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