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Open AccessArticle

Online Home Appliance Control Using EEG-Based Brain–Computer Interfaces

1
Department of Human Factors Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
2
Department of Electrical Engineering, Soonchunhyang University, Asan 31538, Korea
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(10), 1101; https://doi.org/10.3390/electronics8101101
Received: 4 September 2019 / Revised: 28 September 2019 / Accepted: 28 September 2019 / Published: 30 September 2019
Brain–computer interfaces (BCIs) allow patients with paralysis to control external devices by mental commands. Recent advances in home automation and the Internet of things may extend the horizon of BCI applications into daily living environments at home. In this study, we developed an online BCI based on scalp electroencephalography (EEG) to control home appliances. The BCI users controlled TV channels, a digital door-lock system, and an electric light system in an unshielded environment. The BCI was designed to harness P300 and N200 components of event-related potentials (ERPs). On average, the BCI users could control TV channels with an accuracy of 83.0% ± 17.9%, the digital door-lock with 78.7% ± 16.2% accuracy, and the light with 80.0% ± 15.6% accuracy, respectively. Our study demonstrates a feasibility to control multiple home appliances using EEG-based BCIs. View Full-Text
Keywords: brain–computer interface; electroencephalography; home appliance; TV; digital door-lock; electric light; event-related potential brain–computer interface; electroencephalography; home appliance; TV; digital door-lock; electric light; event-related potential
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Kim, M.; Kim, M.-K.; Hwang, M.; Kim, H.-Y.; Cho, J.; Kim, S.-P. Online Home Appliance Control Using EEG-Based Brain–Computer Interfaces. Electronics 2019, 8, 1101.

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