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pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data
In many biomechanical analyses, the forces acting on a body during dynamic and static activities are often simplified as point loads. However, it is usually more accurate to characterize these forces as distributed loads, varying in magnitude and direction, over a given contact area. Evaluating thes...
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/PMC10556014/ https://www.ncbi.nlm.nih.gov/pubmed/37798383 http://dx.doi.org/10.1038/s41598-023-44041-6 |
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author | Telfer, Scott Li, Ellen Y. |
author_facet | Telfer, Scott Li, Ellen Y. |
author_sort | Telfer, Scott |
collection | PubMed |
description | In many biomechanical analyses, the forces acting on a body during dynamic and static activities are often simplified as point loads. However, it is usually more accurate to characterize these forces as distributed loads, varying in magnitude and direction, over a given contact area. Evaluating these pressure distributions while they are applied to different parts of the body can provide effective insights for clinicians and researchers when studying health and disease conditions, for example when investigating the biomechanical factors that may lead to plantar ulceration in diabetic foot disease. At present, most processing and analysis for pressure data is performed using proprietary software, limiting reproducibility, transparency, and consistency across different studies. This paper describes an open-source software package, ‘pressuRe’, which is built in the freely available R statistical computing environment and is designed to process, analyze, and visualize pressure data collected on a range of different hardware systems in a standardized manner. We demonstrate the use of the package on pressure dataset from patients with diabetic foot disease, comparing pressure variables between those with longer and shorter durations of the disease. The results matched closely with those from commercially available software, and individuals with longer duration of diabetes were found to have higher forefoot pressures than those with shorter duration. By utilizing R’s powerful and openly available tools for statistical analysis and user customization, this package may be a useful tool for researchers and clinicians studying plantar pressures and other pressure sensor array based biomechanical measurements. With regular updates intended, this package allows for continued improvement and we welcome feedback and future contributions to extend its scope. In this article, we detail the package’s features and functionality. |
format | Online Article Text |
id | pubmed-10556014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105560142023-10-07 pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data Telfer, Scott Li, Ellen Y. Sci Rep Article In many biomechanical analyses, the forces acting on a body during dynamic and static activities are often simplified as point loads. However, it is usually more accurate to characterize these forces as distributed loads, varying in magnitude and direction, over a given contact area. Evaluating these pressure distributions while they are applied to different parts of the body can provide effective insights for clinicians and researchers when studying health and disease conditions, for example when investigating the biomechanical factors that may lead to plantar ulceration in diabetic foot disease. At present, most processing and analysis for pressure data is performed using proprietary software, limiting reproducibility, transparency, and consistency across different studies. This paper describes an open-source software package, ‘pressuRe’, which is built in the freely available R statistical computing environment and is designed to process, analyze, and visualize pressure data collected on a range of different hardware systems in a standardized manner. We demonstrate the use of the package on pressure dataset from patients with diabetic foot disease, comparing pressure variables between those with longer and shorter durations of the disease. The results matched closely with those from commercially available software, and individuals with longer duration of diabetes were found to have higher forefoot pressures than those with shorter duration. By utilizing R’s powerful and openly available tools for statistical analysis and user customization, this package may be a useful tool for researchers and clinicians studying plantar pressures and other pressure sensor array based biomechanical measurements. With regular updates intended, this package allows for continued improvement and we welcome feedback and future contributions to extend its scope. In this article, we detail the package’s features and functionality. Nature Publishing Group UK 2023-10-05 /pmc/articles/PMC10556014/ /pubmed/37798383 http://dx.doi.org/10.1038/s41598-023-44041-6 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Telfer, Scott Li, Ellen Y. pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data |
title | pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data |
title_full | pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data |
title_fullStr | pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data |
title_full_unstemmed | pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data |
title_short | pressuRe: an R package for analyzing and visualizing biomechanical pressure distribution data |
title_sort | pressure: an r package for analyzing and visualizing biomechanical pressure distribution data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10556014/ https://www.ncbi.nlm.nih.gov/pubmed/37798383 http://dx.doi.org/10.1038/s41598-023-44041-6 |
work_keys_str_mv | AT telferscott pressureanrpackageforanalyzingandvisualizingbiomechanicalpressuredistributiondata AT lielleny pressureanrpackageforanalyzingandvisualizingbiomechanicalpressuredistributiondata |