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Forearm sEMG data from young healthy humans during the execution of hand movements
This work provides a complete dataset containing surface electromyography (sEMG) signals acquired from the forearm with a sampling frequency of 1000 Hz. The dataset is named WyoFlex sEMG Hand Gesture and recorded the data of 28 participants between 18 and 37 years old without neuromuscular diseases...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199907/ https://www.ncbi.nlm.nih.gov/pubmed/37210582 http://dx.doi.org/10.1038/s41597-023-02223-x |
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author | Gomez-Correa, Manuela Ballesteros, Mariana Salgado, Ivan Cruz-Ortiz, David |
author_facet | Gomez-Correa, Manuela Ballesteros, Mariana Salgado, Ivan Cruz-Ortiz, David |
author_sort | Gomez-Correa, Manuela |
collection | PubMed |
description | This work provides a complete dataset containing surface electromyography (sEMG) signals acquired from the forearm with a sampling frequency of 1000 Hz. The dataset is named WyoFlex sEMG Hand Gesture and recorded the data of 28 participants between 18 and 37 years old without neuromuscular diseases or cardiovascular problems. The test protocol consisted of sEMG signals acquisition corresponding to ten wrist and grasping movements (extension, flexion, ulnar deviation, radial deviation, hook grip, power grip, spherical grip, precision grip, lateral grip, and pinch grip), considering three repetitions for each gesture. Also, the dataset contains general information such as anthropometric measures of the upper limb, gender, age, laterally of the person, and physical condition. Likewise, the implemented acquisition system consists of a portable armband with four sEMG channels distributed equidistantly for each forearm. The database could be used for the recognition of hand gestures, evaluation of the evolution of patients in rehabilitation processes, control of upper limb orthoses or prostheses, and biomechanical analysis of the forearm. |
format | Online Article Text |
id | pubmed-10199907 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101999072023-05-22 Forearm sEMG data from young healthy humans during the execution of hand movements Gomez-Correa, Manuela Ballesteros, Mariana Salgado, Ivan Cruz-Ortiz, David Sci Data Data Descriptor This work provides a complete dataset containing surface electromyography (sEMG) signals acquired from the forearm with a sampling frequency of 1000 Hz. The dataset is named WyoFlex sEMG Hand Gesture and recorded the data of 28 participants between 18 and 37 years old without neuromuscular diseases or cardiovascular problems. The test protocol consisted of sEMG signals acquisition corresponding to ten wrist and grasping movements (extension, flexion, ulnar deviation, radial deviation, hook grip, power grip, spherical grip, precision grip, lateral grip, and pinch grip), considering three repetitions for each gesture. Also, the dataset contains general information such as anthropometric measures of the upper limb, gender, age, laterally of the person, and physical condition. Likewise, the implemented acquisition system consists of a portable armband with four sEMG channels distributed equidistantly for each forearm. The database could be used for the recognition of hand gestures, evaluation of the evolution of patients in rehabilitation processes, control of upper limb orthoses or prostheses, and biomechanical analysis of the forearm. Nature Publishing Group UK 2023-05-20 /pmc/articles/PMC10199907/ /pubmed/37210582 http://dx.doi.org/10.1038/s41597-023-02223-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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. The 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Gomez-Correa, Manuela Ballesteros, Mariana Salgado, Ivan Cruz-Ortiz, David Forearm sEMG data from young healthy humans during the execution of hand movements |
title | Forearm sEMG data from young healthy humans during the execution of hand movements |
title_full | Forearm sEMG data from young healthy humans during the execution of hand movements |
title_fullStr | Forearm sEMG data from young healthy humans during the execution of hand movements |
title_full_unstemmed | Forearm sEMG data from young healthy humans during the execution of hand movements |
title_short | Forearm sEMG data from young healthy humans during the execution of hand movements |
title_sort | forearm semg data from young healthy humans during the execution of hand movements |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199907/ https://www.ncbi.nlm.nih.gov/pubmed/37210582 http://dx.doi.org/10.1038/s41597-023-02223-x |
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