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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 (...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2014
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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 |
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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 |
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