Abstract
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.
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Acknowledgments
This research was partly supported by Ministry of Science and Technology in Taiwan, under grants MOST 103-2221-E-009-035-MY2, and MOST 104-2221-E-305-006. This research was also partly supported by Southern Taiwan Science Park Bureau, Tainan, Taiwan, under the grant CZ-12-12-22-103.
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This article is part of the Topical Collection on Systems-Level Quality Improvement
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Lin, BS., Pan, JS., Chu, TY. et al. Development of a Wearable Motor-Imagery-Based Brain–Computer Interface. J Med Syst 40, 71 (2016). https://doi.org/10.1007/s10916-015-0429-6
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DOI: https://doi.org/10.1007/s10916-015-0429-6