Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing

Active balance control is critical for performing many of our everyday activities. Our nervous systems rely on multiple sensory inputs to inform cortical processing, leading to coordinated muscle actions that maintain balance. However, such cortical processing can be challenging to record during mob...

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Autores principales:	Steven M. Peterson, Daniel P. Ferris
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Mobile brain/body imaging Electroencephalography Electromyography Electrooculography Motion capture Independent component analysis Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/f13021780c5c4676ba261adb9ff9fdb7
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spelling	oai:doaj.org-article:f13021780c5c4676ba261adb9ff9fdb72021-11-28T04:33:29ZHuman electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing2352-340910.1016/j.dib.2021.107635https://doaj.org/article/f13021780c5c4676ba261adb9ff9fdb72021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352340921009100https://doaj.org/toc/2352-3409Active balance control is critical for performing many of our everyday activities. Our nervous systems rely on multiple sensory inputs to inform cortical processing, leading to coordinated muscle actions that maintain balance. However, such cortical processing can be challenging to record during mobile balance tasks due to limitations in noninvasive neuroimaging and motion artifact contamination. Here, we present a synchronized, multi-modal dataset from 30 healthy, young human participants during standing and walking while undergoing brief sensorimotor perturbations. Our dataset includes 20 total hours of high-density electroencephalography (EEG) recorded from 128 scalp electrodes, along with surface electromyography (EMG) from 10 neck and leg electrodes, electrooculography (EOG) recorded from 3 electrodes, and 3D body position from 2 sensors. In addition, we include ∼18000 total balance perturbation events across participants. To facilitate data reuse, we share this dataset in the Brain Imaging Data Structure (BIDS) data standard and publicly release code that replicates our previous event-related findings.Steven M. PetersonDaniel P. FerrisElsevierarticleMobile brain/body imagingElectroencephalographyElectromyographyElectrooculographyMotion captureIndependent component analysisComputer applications to medicine. Medical informaticsR858-859.7Science (General)Q1-390ENData in Brief, Vol 39, Iss , Pp 107635- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mobile brain/body imaging Electroencephalography Electromyography Electrooculography Motion capture Independent component analysis Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390
spellingShingle	Mobile brain/body imaging Electroencephalography Electromyography Electrooculography Motion capture Independent component analysis Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390 Steven M. Peterson Daniel P. Ferris Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing
description	Active balance control is critical for performing many of our everyday activities. Our nervous systems rely on multiple sensory inputs to inform cortical processing, leading to coordinated muscle actions that maintain balance. However, such cortical processing can be challenging to record during mobile balance tasks due to limitations in noninvasive neuroimaging and motion artifact contamination. Here, we present a synchronized, multi-modal dataset from 30 healthy, young human participants during standing and walking while undergoing brief sensorimotor perturbations. Our dataset includes 20 total hours of high-density electroencephalography (EEG) recorded from 128 scalp electrodes, along with surface electromyography (EMG) from 10 neck and leg electrodes, electrooculography (EOG) recorded from 3 electrodes, and 3D body position from 2 sensors. In addition, we include ∼18000 total balance perturbation events across participants. To facilitate data reuse, we share this dataset in the Brain Imaging Data Structure (BIDS) data standard and publicly release code that replicates our previous event-related findings.
format	article
author	Steven M. Peterson Daniel P. Ferris
author_facet	Steven M. Peterson Daniel P. Ferris
author_sort	Steven M. Peterson
title	Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing
title_short	Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing
title_full	Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing
title_fullStr	Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing
title_full_unstemmed	Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing
title_sort	human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/f13021780c5c4676ba261adb9ff9fdb7
work_keys_str_mv	AT stevenmpeterson humanelectrocorticalelectromyographicalocularandkinematicdataduringperturbedwalkingandstanding AT danielpferris humanelectrocorticalelectromyographicalocularandkinematicdataduringperturbedwalkingandstanding
_version_	1718408354427043840

Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing

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