An N100-P300 Spelling Brain-Computer Interface with Detection of Intentional Control
Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan
Author to whom correspondence should be addressed.
Academic Editor: Sebastian Halder
Received: 1 October 2016 / Revised: 18 November 2016 / Accepted: 24 November 2016 / Published: 2 December 2016
A brain-computer interface (BCI) is a tool to communicate with a computer via brain signals without the user making any physical movements, thus enabling disabled people to communicate with their environment and with others. P300-based ERP spellers are a widely used spelling visual BCI using the P300 component of event-related potential (ERP). However, they have a technical problem in that at least
flashes are required to present N
characters. This prevents the improvement of accuracy and restricts the typing speed. To address this issue, we propose a method that uses N100 in addition to P300. We utilize novel stimulus images to detect the user’s gazing position by using N100. By using both P300 and N100, the proposed visual BCI reduces the number of flashes and improves the accuracy of the P300 speller. We also propose using N100 to classify non-control (NC) and intentional control (IC) states. In our experiments, the detection accuracy of N100 was significantly higher than that of P300 and the proposed method exhibited a higher information transfer rate (ITR) than the P300 speller.
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MDPI and ACS Style
Sato, H.; Washizawa, Y. An N100-P300 Spelling Brain-Computer Interface with Detection of Intentional Control. Computers 2016, 5, 31.
Sato H, Washizawa Y. An N100-P300 Spelling Brain-Computer Interface with Detection of Intentional Control. Computers. 2016; 5(4):31.
Sato, Hikaru; Washizawa, Yoshikazu. 2016. "An N100-P300 Spelling Brain-Computer Interface with Detection of Intentional Control." Computers 5, no. 4: 31.
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