Cargando…

Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction

WAY-EEG-GAL is a dataset designed to allow critical tests of techniques to decode sensation, intention, and action from scalp EEG recordings in humans who perform a grasp-and-lift task. Twelve participants performed lifting series in which the object’s weight (165, 330, or 660 g), surface friction (...

Descripción completa

Detalles Bibliográficos
Autores principales: Luciw, Matthew D, Jarocka, Ewa, Edin, Benoni B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4365902/
https://www.ncbi.nlm.nih.gov/pubmed/25977798
http://dx.doi.org/10.1038/sdata.2014.47
_version_ 1782362293816786944
author Luciw, Matthew D
Jarocka, Ewa
Edin, Benoni B
author_facet Luciw, Matthew D
Jarocka, Ewa
Edin, Benoni B
author_sort Luciw, Matthew D
collection PubMed
description WAY-EEG-GAL is a dataset designed to allow critical tests of techniques to decode sensation, intention, and action from scalp EEG recordings in humans who perform a grasp-and-lift task. Twelve participants performed lifting series in which the object’s weight (165, 330, or 660 g), surface friction (sandpaper, suede, or silk surface), or both, were changed unpredictably between trials, thus enforcing changes in fingertip force coordination. In each of a total of 3,936 trials, the participant was cued to reach for the object, grasp it with the thumb and index finger, lift it and hold it for a couple of seconds, put it back on the support surface, release it, and, lastly, to return the hand to a designated rest position. We recorded EEG (32 channels), EMG (five arm and hand muscles), the 3D position of both the hand and object, and force/torque at both contact plates. For each trial we provide 16 event times (e.g., ‘object lift-off’) and 18 measures that characterize the behaviour (e.g., ‘peak grip force’).
format Online
Article
Text
id pubmed-4365902
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-43659022015-05-14 Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction Luciw, Matthew D Jarocka, Ewa Edin, Benoni B Sci Data Data Descriptor WAY-EEG-GAL is a dataset designed to allow critical tests of techniques to decode sensation, intention, and action from scalp EEG recordings in humans who perform a grasp-and-lift task. Twelve participants performed lifting series in which the object’s weight (165, 330, or 660 g), surface friction (sandpaper, suede, or silk surface), or both, were changed unpredictably between trials, thus enforcing changes in fingertip force coordination. In each of a total of 3,936 trials, the participant was cued to reach for the object, grasp it with the thumb and index finger, lift it and hold it for a couple of seconds, put it back on the support surface, release it, and, lastly, to return the hand to a designated rest position. We recorded EEG (32 channels), EMG (five arm and hand muscles), the 3D position of both the hand and object, and force/torque at both contact plates. For each trial we provide 16 event times (e.g., ‘object lift-off’) and 18 measures that characterize the behaviour (e.g., ‘peak grip force’). Nature Publishing Group 2014-11-25 /pmc/articles/PMC4365902/ /pubmed/25977798 http://dx.doi.org/10.1038/sdata.2014.47 Text en Copyright © 2014, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse.
spellingShingle Data Descriptor
Luciw, Matthew D
Jarocka, Ewa
Edin, Benoni B
Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction
title Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction
title_full Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction
title_fullStr Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction
title_full_unstemmed Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction
title_short Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction
title_sort multi-channel eeg recordings during 3,936 grasp and lift trials with varying weight and friction
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4365902/
https://www.ncbi.nlm.nih.gov/pubmed/25977798
http://dx.doi.org/10.1038/sdata.2014.47
work_keys_str_mv AT luciwmatthewd multichanneleegrecordingsduring3936graspandlifttrialswithvaryingweightandfriction
AT jarockaewa multichanneleegrecordingsduring3936graspandlifttrialswithvaryingweightandfriction
AT edinbenonib multichanneleegrecordingsduring3936graspandlifttrialswithvaryingweightandfriction