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A dataset of EEG signals from a single-channel SSVEP-based brain computer interface

The paper presents a collection of electroencephalography (EEG) data from a portable Steady State Visual Evoked Potentials (SSVEP)-based Brain Computer Interface (BCI). The collection of data was acquired by means of experiments based on repetitive visual stimuli with four different flickering frequ...

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Detalles Bibliográficos
Autores principales: Acampora, Giovanni, Trinchese, Pasquale, Vitiello, Autilia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890157/
https://www.ncbi.nlm.nih.gov/pubmed/33659590
http://dx.doi.org/10.1016/j.dib.2021.106826
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author Acampora, Giovanni
Trinchese, Pasquale
Vitiello, Autilia
author_facet Acampora, Giovanni
Trinchese, Pasquale
Vitiello, Autilia
author_sort Acampora, Giovanni
collection PubMed
description The paper presents a collection of electroencephalography (EEG) data from a portable Steady State Visual Evoked Potentials (SSVEP)-based Brain Computer Interface (BCI). The collection of data was acquired by means of experiments based on repetitive visual stimuli with four different flickering frequencies. The main novelty of the proposed data set is related to the usage of a single-channel dry-sensor acquisition device. Different from conventional BCI helmets, this kind of device strongly improves the users’ comfort and, therefore, there is a strong interest in using it to pave the way towards the future generation of Internet of Things (IoT) applications. Consequently, the dataset proposed in this paper aims to act as a key tool to support the research activities in this emerging topic of human-computer interaction.
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spelling pubmed-78901572021-03-02 A dataset of EEG signals from a single-channel SSVEP-based brain computer interface Acampora, Giovanni Trinchese, Pasquale Vitiello, Autilia Data Brief Data Article The paper presents a collection of electroencephalography (EEG) data from a portable Steady State Visual Evoked Potentials (SSVEP)-based Brain Computer Interface (BCI). The collection of data was acquired by means of experiments based on repetitive visual stimuli with four different flickering frequencies. The main novelty of the proposed data set is related to the usage of a single-channel dry-sensor acquisition device. Different from conventional BCI helmets, this kind of device strongly improves the users’ comfort and, therefore, there is a strong interest in using it to pave the way towards the future generation of Internet of Things (IoT) applications. Consequently, the dataset proposed in this paper aims to act as a key tool to support the research activities in this emerging topic of human-computer interaction. Elsevier 2021-02-02 /pmc/articles/PMC7890157/ /pubmed/33659590 http://dx.doi.org/10.1016/j.dib.2021.106826 Text en © 2021 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Acampora, Giovanni
Trinchese, Pasquale
Vitiello, Autilia
A dataset of EEG signals from a single-channel SSVEP-based brain computer interface
title A dataset of EEG signals from a single-channel SSVEP-based brain computer interface
title_full A dataset of EEG signals from a single-channel SSVEP-based brain computer interface
title_fullStr A dataset of EEG signals from a single-channel SSVEP-based brain computer interface
title_full_unstemmed A dataset of EEG signals from a single-channel SSVEP-based brain computer interface
title_short A dataset of EEG signals from a single-channel SSVEP-based brain computer interface
title_sort dataset of eeg signals from a single-channel ssvep-based brain computer interface
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890157/
https://www.ncbi.nlm.nih.gov/pubmed/33659590
http://dx.doi.org/10.1016/j.dib.2021.106826
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