Next Article in Journal
BSEA: A Blind Sealed-Bid E-Auction Scheme for E-Commerce Applications
Previous Article in Journal
Store-Carry and Forward-Type M2M Communication Protocol Enabling Guide Robots to Work together and the Method of Identifying Malfunctioning Robots Using the Byzantine Algorithm
Article Menu

Export Article

Open AccessArticle
Computers 2016, 5(4), 31; doi:10.3390/computers5040031

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
(This article belongs to the Special Issue Event-Related Potential Brain-Computer Interfaces)
View Full-Text   |   Download PDF [1672 KB, uploaded 2 December 2016]   |  

Abstract

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 2 N 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. View Full-Text
Keywords: visual evoked potintials (VEP); N100; P300; brain computer interface (BCI); intentional-control (IC); self-paced BCI; P300 speller visual evoked potintials (VEP); N100; P300; brain computer interface (BCI); intentional-control (IC); self-paced BCI; P300 speller
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Sato, H.; Washizawa, Y. An N100-P300 Spelling Brain-Computer Interface with Detection of Intentional Control. Computers 2016, 5, 31.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Computers EISSN 2073-431X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top