| Summary: | 碩士 === 國立交通大學 === 電子工程學系 電子研究所 === 103 === Stroke rehabilitation with EEG-based brain computer interface enables interaction through brain signals and restoration of motor function of the brain. However, conventional approaches require high complexity for reliable detection and fail to achieve real time response. This thesis proposes a real time low complexity BCI interface for stroke rehabilitation.
The proposed approach is based on the filter bank common spatial pattern (FBCSP) method. To reduce complexity, the EEG channels are reduced from 19 channels to 4 channels, Fz, C3, Cz, C4 to detect the movement intention for normal and stroke people with satisfying accuracy. Furthermore, the filter bank is reduced from five bands to three bands, 4~7Hz, 8~12Hz, 13~30Hz to reduce the complexity. A real time on-line scheme is developed with above method that uses one second time window for EEG analysis and transition region for smooth BCI control. These approaches saves 90% of computational complexity. The simulation results shows over 80% of accuracy for offline analysis, and 67% accuracy for the on-line approach with less than one second response time.
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