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A large calibrated database of hand movements and grasps kinematics
dc.contributor.author | Jarque-Bou, Néstor J | |
dc.contributor.author | Atzori, Manfredo | |
dc.contributor.author | Müller, Henning | |
dc.date.accessioned | 2020-11-24T18:14:45Z | |
dc.date.available | 2020-11-24T18:14:45Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | JARQUE-BOU, Néstor J.; ATZORI, Manfredo; MÜLLER, Henning. A large calibrated database of hand movements and grasps kinematics. Scientific Data, 2020, vol. 7, núm. 1, p. 1-10 | ca_CA |
dc.identifier.issn | 2052-4463 | |
dc.identifier.uri | http://hdl.handle.net/10234/190466 | |
dc.description.abstract | Modelling hand kinematics is a challenging problem, crucial for several domains including robotics, 3D modelling, rehabilitation medicine and neuroscience. Currently available datasets are few and limited in the number of subjects and movements. The objective of this work is to advance the modelling of hand kinematics by releasing and validating a large publicly available kinematic dataset of hand movements and grasp kinematics. The dataset is based on the harmonization and calibration of the kinematics data of three multimodal datasets previously released (Ninapro DB1, DB2 and DB5, that include electromyography, inertial and dynamic data). The novelty of the dataset is related to the high number of subjects (77) and movements (40 movements, each repeated several times) for which we release for the frst time calibrated kinematic data, resulting in the largest available kinematic dataset. Diferently from the previous datasets, the data are also calibrated to avoid sensor nonlinearities. The validation confrms that the data are not afected by experimental procedures and that they are similar to data acquired in real-life conditions. | ca_CA |
dc.format.extent | 10 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Nature Research | ca_CA |
dc.relation.isPartOf | Scientific Data, 2020, vol. 7, no 1, p. 1-10 | ca_CA |
dc.rights | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata fles associated with this article. © The Author(s) 2020 | ca_CA |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/ | * |
dc.title | A large calibrated database of hand movements and grasps kinematics | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.6084/m9.figshare.11341679 | |
dc.relation.projectID | This work was partially supported by the Swiss National Science Foundation Sinergia project #410160837 MeganePro. Te authors are also grateful for funding received from the Spanish MINECO and the European Union (FEDER funds) through project DPI2014-52095-P and FPI grant BES-2015-072480. | ca_CA |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://www.nature.com/articles/s41597-019-0349-2 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this
article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the
copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/
applies to the metadata fles associated with this article.
© The Author(s) 2020