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High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions
Valid approaches for interfacing with and deciphering neural commands related to movement are critical to understanding muscular coordination and developing viable prostheses and wearable robotics. While electromyography (EMG) has been an established approach for mapping neural input to mechanical o...
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/PMC10326057/ https://www.ncbi.nlm.nih.gov/pubmed/37414829 http://dx.doi.org/10.1038/s41597-023-02114-1 |
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author | Bradford, J. Cortney Tweedell, Andrew Leahy, Logan |
author_facet | Bradford, J. Cortney Tweedell, Andrew Leahy, Logan |
author_sort | Bradford, J. Cortney |
collection | PubMed |
description | Valid approaches for interfacing with and deciphering neural commands related to movement are critical to understanding muscular coordination and developing viable prostheses and wearable robotics. While electromyography (EMG) has been an established approach for mapping neural input to mechanical output, there is a lack of adaptability to dynamic environments due to a lack of data from dynamic movements. This report presents data consisting of simultaneously recorded high density surface EMG, intramuscular EMG, and joint dynamics from the tibialis anterior during static and dynamic muscle contractions. The dataset comes from seven subjects performing three to five trials each of different types of muscle contractions, both static (isometric) and dynamic (isotonic and isokinetic). Each subject was seated in an isokinetic dynamometer such that ankle movement was isolated and instrumented with four fine wire electrodes and a 126-electrode surface EMG grid. This data set can be used to (i) validate methods for extracting neural signals from surface EMG, (ii) develop models for predicting torque output, or (iii) develop classifiers for movement intent. |
format | Online Article Text |
id | pubmed-10326057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103260572023-07-08 High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions Bradford, J. Cortney Tweedell, Andrew Leahy, Logan Sci Data Data Descriptor Valid approaches for interfacing with and deciphering neural commands related to movement are critical to understanding muscular coordination and developing viable prostheses and wearable robotics. While electromyography (EMG) has been an established approach for mapping neural input to mechanical output, there is a lack of adaptability to dynamic environments due to a lack of data from dynamic movements. This report presents data consisting of simultaneously recorded high density surface EMG, intramuscular EMG, and joint dynamics from the tibialis anterior during static and dynamic muscle contractions. The dataset comes from seven subjects performing three to five trials each of different types of muscle contractions, both static (isometric) and dynamic (isotonic and isokinetic). Each subject was seated in an isokinetic dynamometer such that ankle movement was isolated and instrumented with four fine wire electrodes and a 126-electrode surface EMG grid. This data set can be used to (i) validate methods for extracting neural signals from surface EMG, (ii) develop models for predicting torque output, or (iii) develop classifiers for movement intent. Nature Publishing Group UK 2023-07-06 /pmc/articles/PMC10326057/ /pubmed/37414829 http://dx.doi.org/10.1038/s41597-023-02114-1 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 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 Bradford, J. Cortney Tweedell, Andrew Leahy, Logan High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions |
title | High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions |
title_full | High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions |
title_fullStr | High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions |
title_full_unstemmed | High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions |
title_short | High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions |
title_sort | high-density surface and intramuscular emg data from the tibialis anterior during dynamic contractions |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10326057/ https://www.ncbi.nlm.nih.gov/pubmed/37414829 http://dx.doi.org/10.1038/s41597-023-02114-1 |
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