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|Title:||BCI-FES training system design and implementation for rehabilitation of stroke patients|
Tong, Kai-yu Raymond
Chan, Suk-tak Phoebe
Medical signal processing
|Source:||Proceedings of the International Joint Conference on Neural Networks, IJCNN 2008 (IEEE World Congress on Computational Intelligence) : Hong Kong, China, June, 2008, p. 4103-4106.|
|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 users' 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.|
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|Appears in Collections:||HTI Conference Papers & Presentations|
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