Journal
ELECTRONICS
Volume 8, Issue 10, Pages -Publisher
MDPI
DOI: 10.3390/electronics8101101
Keywords
brain-computer interface; electroencephalography; home appliance; TV; digital door-lock; electric light; event-related potential
Categories
Funding
- Institute of Information and Communications Technology Planning and Evaluation (IITP) - Korean government (MSIT) [2017-0-00432]
- UNIST (Ulsan National Institute of Science and Technology) [1.190042.01]
- Institute for Information & Communication Technology Planning & Evaluation (IITP), Republic of Korea [2017-0-00432-003] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [2019UNIST 연구브랜드 육성(UK)] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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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.
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