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EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface

We usually look at an object when we are going to manipulate it. Thus, eye tracking can be used to communicate intended actions. An effective human-machine interface, however, should be able to differentiate intentional and spontaneous eye movements. We report an electroencephalogram (EEG) marker th...

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Autores principales: Shishkin, Sergei L., Nuzhdin, Yuri O., Svirin, Evgeny P., Trofimov, Alexander G., Fedorova, Anastasia A., Kozyrskiy, Bogdan L., Velichkovsky, Boris M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5114310/
https://www.ncbi.nlm.nih.gov/pubmed/27917105
http://dx.doi.org/10.3389/fnins.2016.00528
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author Shishkin, Sergei L.
Nuzhdin, Yuri O.
Svirin, Evgeny P.
Trofimov, Alexander G.
Fedorova, Anastasia A.
Kozyrskiy, Bogdan L.
Velichkovsky, Boris M.
author_facet Shishkin, Sergei L.
Nuzhdin, Yuri O.
Svirin, Evgeny P.
Trofimov, Alexander G.
Fedorova, Anastasia A.
Kozyrskiy, Bogdan L.
Velichkovsky, Boris M.
author_sort Shishkin, Sergei L.
collection PubMed
description We usually look at an object when we are going to manipulate it. Thus, eye tracking can be used to communicate intended actions. An effective human-machine interface, however, should be able to differentiate intentional and spontaneous eye movements. We report an electroencephalogram (EEG) marker that differentiates gaze fixations used for control from spontaneous fixations involved in visual exploration. Eight healthy participants played a game with their eye movements only. Their gaze-synchronized EEG data (fixation-related potentials, FRPs) were collected during game's control-on and control-off conditions. A slow negative wave with a maximum in the parietooccipital region was present in each participant's averaged FRPs in the control-on conditions and was absent or had much lower amplitude in the control-off condition. This wave was similar but not identical to stimulus-preceding negativity, a slow negative wave that can be observed during feedback expectation. Classification of intentional vs. spontaneous fixations was based on amplitude features from 13 EEG channels using 300 ms length segments free from electrooculogram contamination (200–500 ms relative to the fixation onset). For the first fixations in the fixation triplets required to make moves in the game, classified against control-off data, a committee of greedy classifiers provided 0.90 ± 0.07 specificity and 0.38 ± 0.14 sensitivity. Similar (slightly lower) results were obtained for the shrinkage Linear Discriminate Analysis (LDA) classifier. The second and third fixations in the triplets were classified at lower rate. We expect that, with improved feature sets and classifiers, a hybrid dwell-based Eye-Brain-Computer Interface (EBCI) can be built using the FRP difference between the intended and spontaneous fixations. If this direction of BCI development will be successful, such a multimodal interface may improve the fluency of interaction and can possibly become the basis for a new input device for paralyzed and healthy users, the EBCI “Wish Mouse.”
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spelling pubmed-51143102016-12-02 EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface Shishkin, Sergei L. Nuzhdin, Yuri O. Svirin, Evgeny P. Trofimov, Alexander G. Fedorova, Anastasia A. Kozyrskiy, Bogdan L. Velichkovsky, Boris M. Front Neurosci Neuroscience We usually look at an object when we are going to manipulate it. Thus, eye tracking can be used to communicate intended actions. An effective human-machine interface, however, should be able to differentiate intentional and spontaneous eye movements. We report an electroencephalogram (EEG) marker that differentiates gaze fixations used for control from spontaneous fixations involved in visual exploration. Eight healthy participants played a game with their eye movements only. Their gaze-synchronized EEG data (fixation-related potentials, FRPs) were collected during game's control-on and control-off conditions. A slow negative wave with a maximum in the parietooccipital region was present in each participant's averaged FRPs in the control-on conditions and was absent or had much lower amplitude in the control-off condition. This wave was similar but not identical to stimulus-preceding negativity, a slow negative wave that can be observed during feedback expectation. Classification of intentional vs. spontaneous fixations was based on amplitude features from 13 EEG channels using 300 ms length segments free from electrooculogram contamination (200–500 ms relative to the fixation onset). For the first fixations in the fixation triplets required to make moves in the game, classified against control-off data, a committee of greedy classifiers provided 0.90 ± 0.07 specificity and 0.38 ± 0.14 sensitivity. Similar (slightly lower) results were obtained for the shrinkage Linear Discriminate Analysis (LDA) classifier. The second and third fixations in the triplets were classified at lower rate. We expect that, with improved feature sets and classifiers, a hybrid dwell-based Eye-Brain-Computer Interface (EBCI) can be built using the FRP difference between the intended and spontaneous fixations. If this direction of BCI development will be successful, such a multimodal interface may improve the fluency of interaction and can possibly become the basis for a new input device for paralyzed and healthy users, the EBCI “Wish Mouse.” Frontiers Media S.A. 2016-11-18 /pmc/articles/PMC5114310/ /pubmed/27917105 http://dx.doi.org/10.3389/fnins.2016.00528 Text en Copyright © 2016 Shishkin, Nuzhdin, Svirin, Trofimov, Fedorova, Kozyrskiy and Velichkovsky. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Shishkin, Sergei L.
Nuzhdin, Yuri O.
Svirin, Evgeny P.
Trofimov, Alexander G.
Fedorova, Anastasia A.
Kozyrskiy, Bogdan L.
Velichkovsky, Boris M.
EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface
title EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface
title_full EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface
title_fullStr EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface
title_full_unstemmed EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface
title_short EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface
title_sort eeg negativity in fixations used for gaze-based control: toward converting intentions into actions with an eye-brain-computer interface
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5114310/
https://www.ncbi.nlm.nih.gov/pubmed/27917105
http://dx.doi.org/10.3389/fnins.2016.00528
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