Nur Syazreen Ahmad*, Jia Hui Teo, Patrick Goh
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 611-628, 2022, DOI:10.32604/cmc.2022.025823
Abstract A single-channel electroencephalography (EEG) device, despite being widely accepted due to convenience, ease of deployment and suitability for use in complex environments, typically poses a great challenge for reactive brain-computer interface (BCI) applications particularly when a continuous command from users is desired to run a motorized actuator with different speed profiles. In this study, a combination of an inconspicuous visual stimulus and voluntary eyeblinks along with a machine learning-based decoder is considered as a new reactive BCI paradigm to increase the degree of freedom and minimize mismatches between the intended dynamic command and transmitted control signal. The proposed decoder is… More >
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