Application of a single-flicker online SSVEP BCI for spatial navigation.

A promising approach for brain-computer interfaces (BCIs) employs the steady-state visual evoked potential (SSVEP) for extracting control information. Main advantages of these SSVEP BCIs are a simple and low-cost setup, little effort to adjust the system parameters to the user and comparatively high...

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Main Authors: Jingjing Chen, Dan Zhang, Andreas K Engel, Qin Gong, Alexander Maye
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5451069?pdf=render
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spelling doaj-7431456d672f4a4eb278e1768073ce3d2020-11-25T02:05:17ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01125e017838510.1371/journal.pone.0178385Application of a single-flicker online SSVEP BCI for spatial navigation.Jingjing ChenDan ZhangAndreas K EngelQin GongAlexander MayeA promising approach for brain-computer interfaces (BCIs) employs the steady-state visual evoked potential (SSVEP) for extracting control information. Main advantages of these SSVEP BCIs are a simple and low-cost setup, little effort to adjust the system parameters to the user and comparatively high information transfer rates (ITR). However, traditional frequency-coded SSVEP BCIs require the user to gaze directly at the selected flicker stimulus, which is liable to cause fatigue or even photic epileptic seizures. The spatially coded SSVEP BCI we present in this article addresses this issue. It uses a single flicker stimulus that appears always in the extrafoveal field of view, yet it allows the user to control four control channels. We demonstrate the embedding of this novel SSVEP stimulation paradigm in the user interface of an online BCI for navigating a 2-dimensional computer game. Offline analysis of the training data reveals an average classification accuracy of 96.9±1.64%, corresponding to an information transfer rate of 30.1±1.8 bits/min. In online mode, the average classification accuracy reached 87.9±11.4%, which resulted in an ITR of 23.8±6.75 bits/min. We did not observe a strong relation between a subject's offline and online performance. Analysis of the online performance over time shows that users can reliably control the new BCI paradigm with stable performance over at least 30 minutes of continuous operation.http://europepmc.org/articles/PMC5451069?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Jingjing Chen
Dan Zhang
Andreas K Engel
Qin Gong
Alexander Maye
spellingShingle Jingjing Chen
Dan Zhang
Andreas K Engel
Qin Gong
Alexander Maye
Application of a single-flicker online SSVEP BCI for spatial navigation.
PLoS ONE
author_facet Jingjing Chen
Dan Zhang
Andreas K Engel
Qin Gong
Alexander Maye
author_sort Jingjing Chen
title Application of a single-flicker online SSVEP BCI for spatial navigation.
title_short Application of a single-flicker online SSVEP BCI for spatial navigation.
title_full Application of a single-flicker online SSVEP BCI for spatial navigation.
title_fullStr Application of a single-flicker online SSVEP BCI for spatial navigation.
title_full_unstemmed Application of a single-flicker online SSVEP BCI for spatial navigation.
title_sort application of a single-flicker online ssvep bci for spatial navigation.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description A promising approach for brain-computer interfaces (BCIs) employs the steady-state visual evoked potential (SSVEP) for extracting control information. Main advantages of these SSVEP BCIs are a simple and low-cost setup, little effort to adjust the system parameters to the user and comparatively high information transfer rates (ITR). However, traditional frequency-coded SSVEP BCIs require the user to gaze directly at the selected flicker stimulus, which is liable to cause fatigue or even photic epileptic seizures. The spatially coded SSVEP BCI we present in this article addresses this issue. It uses a single flicker stimulus that appears always in the extrafoveal field of view, yet it allows the user to control four control channels. We demonstrate the embedding of this novel SSVEP stimulation paradigm in the user interface of an online BCI for navigating a 2-dimensional computer game. Offline analysis of the training data reveals an average classification accuracy of 96.9±1.64%, corresponding to an information transfer rate of 30.1±1.8 bits/min. In online mode, the average classification accuracy reached 87.9±11.4%, which resulted in an ITR of 23.8±6.75 bits/min. We did not observe a strong relation between a subject's offline and online performance. Analysis of the online performance over time shows that users can reliably control the new BCI paradigm with stable performance over at least 30 minutes of continuous operation.
url http://europepmc.org/articles/PMC5451069?pdf=render
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