A motor-imagery-based brain–computer interface (BCI) is a translator that converts the motor intention of the brain into a control command to control external machines without muscles. Numerous motor-imagery-based BCIs have been successfully proposed in previous studies. However, several electroencephalogram (EEG) channels are typically required for providing sufficient information to maintain a specific accuracy and bit rate, and the bulk volume of these EEG machines is also inconvenient. A wearable motor imagery-based BCI system was proposed and implemented in this study. A wearable mechanical design with novel active comb-shaped dry electrodes was developed to measure EEG signals without conductive gels at hair sites, which is easy and convenient for users wearing the EEG machine. In addition, a wireless EEG acquisition module was also designed to measure EEG signals, which provides a user with more freedom of motion. The proposed wearable motor-imagery-based BCI system was validated using an electrical specifications test and a hand motor imagery experiment. Experimental results showed that the proposed wearable motor-imagery-based BCI system provides favorable signal quality for measuring EEG signals and detecting motor imagery.
