A steady-state visual evoked potential-based brain-computer interface dataset in children and adolescents

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Abstract The development of steady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) for children has been limited, in part, by the scarcity of publicly available pediatric SSVEP datasets. In addition, an established issue with SSVEP-based BCI systems is the visual fatigue and discomfort caused by high contrast flashing visual stimuli. Here, we present an open-access pediatric SSVEP dataset (n=47; age 5–18 years), comprised of EEG recorded during a standard laboratory-style SSVEP experiment, and a user-choice led online 4-target SSVEP-based game. The standard experiment evaluated 12 SSVEP stimuli varying in contrast and size, weighing comfort ratings with SSVEP signal strength to determine an individualized SSVEP stimulus for each participant. Participants subsequently completed the online SSVEP-based BCI game using both their personalized stimulus and a standard high-contrast stimulus. The signal quality of the dataset was validated through comparisons with two existing SSVEP datasets, demonstrating similar spectral peaks and signal-to-noise ratios at fundamental and harmonic frequencies. This dataset provides EEG data from children aged 5-18 (mean 12.6±3.9) years to support pediatric-specific SSVEP stimulus optimization as well as signal processing advancements in SSVEP-based BCI research.
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A steady-state visual evoked potential-based brain-computer interface dataset in children and adolescents | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF data-descriptor A steady-state visual evoked potential-based brain-computer interface dataset in children and adolescents Emily Schrag, Daniel Comaduran Marquez, Adam Kirton, Eli Kinney-Lang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9347306/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The development of steady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) for children has been limited, in part, by the scarcity of publicly available pediatric SSVEP datasets. In addition, an established issue with SSVEP-based BCI systems is the visual fatigue and discomfort caused by high contrast flashing visual stimuli. Here, we present an open-access pediatric SSVEP dataset (n=47; age 5–18 years), comprised of EEG recorded during a standard laboratory-style SSVEP experiment, and a user-choice led online 4-target SSVEP-based game. The standard experiment evaluated 12 SSVEP stimuli varying in contrast and size, weighing comfort ratings with SSVEP signal strength to determine an individualized SSVEP stimulus for each participant. Participants subsequently completed the online SSVEP-based BCI game using both their personalized stimulus and a standard high-contrast stimulus. The signal quality of the dataset was validated through comparisons with two existing SSVEP datasets, demonstrating similar spectral peaks and signal-to-noise ratios at fundamental and harmonic frequencies. This dataset provides EEG data from children aged 5-18 (mean 12.6±3.9) years to support pediatric-specific SSVEP stimulus optimization as well as signal processing advancements in SSVEP-based BCI research. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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