Abstract
A brain-computer interface (BCI) system can recognize the mental activities pattern by computer algorithms to control the external devices. Electroencephalogram (EEG) is one of the most common used approach for BCI due to the convenience and non-invasive implement. Therefore, more and more BCIs have been designed for the disabled people that suffer from stroke or spinal cord injury to help them for rehabilitation and life. We introduce the common BCI paradigms, the signal processing, and feature extraction methods. Then, we survey the different combined modes of hybrids BCIs and review the design of the synchronous/asynchronous BCIs. Finally, the shared control methods are discussed.
Cite
CITATION STYLE
Zhang, W., Tan, C., Sun, F., Wu, H., & Zhang, B. (2018). A Review of EEG-Based Brain-Computer Interface Systems Design. Brain Science Advances, 4(2), 156–167. https://doi.org/10.26599/bsa.2018.9050010
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