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Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry
BACKGROUND: Range of motion (ROM) measurements are essential for diagnosing and evaluating upper extremity conditions. Clinical goniometry is the most commonly used methods but it is time-consuming and skill-demanding. Recent advances in human tracking algorithm suggest potential for automatic angle...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490917/ https://www.ncbi.nlm.nih.gov/pubmed/36131313 http://dx.doi.org/10.1186/s12891-022-05826-4 |
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author | Fan, Jingyuan Gu, Fanbin Lv, Lulu Zhang, Zhejin Zhu, Changbing Qi, Jian Wang, Honggang Liu, Xiaolin Yang, Jiantao Zhu, Qingtang |
author_facet | Fan, Jingyuan Gu, Fanbin Lv, Lulu Zhang, Zhejin Zhu, Changbing Qi, Jian Wang, Honggang Liu, Xiaolin Yang, Jiantao Zhu, Qingtang |
author_sort | Fan, Jingyuan |
collection | PubMed |
description | BACKGROUND: Range of motion (ROM) measurements are essential for diagnosing and evaluating upper extremity conditions. Clinical goniometry is the most commonly used methods but it is time-consuming and skill-demanding. Recent advances in human tracking algorithm suggest potential for automatic angle measuring from RGB images. It provides an attractive alternative for at-distance measuring. However, the reliability of this method has not been fully established. The purpose of this study is to evaluate if the results of algorithm are as reliable as human raters in upper limb movements. METHODS: Thirty healthy young adults (20 males, 10 females) participated in this study. Participants were asked to performed a 6-motion task including movement of shoulder, elbow and wrist. Images of movements were captured by commercial digital cameras. Each movement was measured by a pose tracking algorithm (OpenPose) and compared with the surgeon-measurement results. The mean differences between the two measurements were compared. Pearson correlation coefficients were used to determine the relationship. Reliability was investigated by the intra-class correlation coefficients. RESULTS: Comparing this algorithm-based method with manual measurement, the mean differences were less than 3 degrees in 5 motions (shoulder abduction: 0.51; shoulder elevation: 2.87; elbow flexion:0.38; elbow extension:0.65; wrist extension: 0.78) except wrist flexion. All the intra-class correlation coefficients were larger than 0.60. The Pearson coefficients also showed high correlations between the two measurements (p < 0.001). CONCLUSIONS: Our results indicated that pose estimation is a reliable method to measure the shoulder and elbow angles, supporting RGB images for measuring joint ROM. Our results presented the possibility that patients can assess their ROM by photos taken by a digital camera. TRIAL REGISTRATION: This study was registered in the Clinical Trials Center of The First Affiliated Hospital, Sun Yat-sen University (2021–387). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-022-05826-4. |
format | Online Article Text |
id | pubmed-9490917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-94909172022-09-22 Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry Fan, Jingyuan Gu, Fanbin Lv, Lulu Zhang, Zhejin Zhu, Changbing Qi, Jian Wang, Honggang Liu, Xiaolin Yang, Jiantao Zhu, Qingtang BMC Musculoskelet Disord Research BACKGROUND: Range of motion (ROM) measurements are essential for diagnosing and evaluating upper extremity conditions. Clinical goniometry is the most commonly used methods but it is time-consuming and skill-demanding. Recent advances in human tracking algorithm suggest potential for automatic angle measuring from RGB images. It provides an attractive alternative for at-distance measuring. However, the reliability of this method has not been fully established. The purpose of this study is to evaluate if the results of algorithm are as reliable as human raters in upper limb movements. METHODS: Thirty healthy young adults (20 males, 10 females) participated in this study. Participants were asked to performed a 6-motion task including movement of shoulder, elbow and wrist. Images of movements were captured by commercial digital cameras. Each movement was measured by a pose tracking algorithm (OpenPose) and compared with the surgeon-measurement results. The mean differences between the two measurements were compared. Pearson correlation coefficients were used to determine the relationship. Reliability was investigated by the intra-class correlation coefficients. RESULTS: Comparing this algorithm-based method with manual measurement, the mean differences were less than 3 degrees in 5 motions (shoulder abduction: 0.51; shoulder elevation: 2.87; elbow flexion:0.38; elbow extension:0.65; wrist extension: 0.78) except wrist flexion. All the intra-class correlation coefficients were larger than 0.60. The Pearson coefficients also showed high correlations between the two measurements (p < 0.001). CONCLUSIONS: Our results indicated that pose estimation is a reliable method to measure the shoulder and elbow angles, supporting RGB images for measuring joint ROM. Our results presented the possibility that patients can assess their ROM by photos taken by a digital camera. TRIAL REGISTRATION: This study was registered in the Clinical Trials Center of The First Affiliated Hospital, Sun Yat-sen University (2021–387). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-022-05826-4. BioMed Central 2022-09-21 /pmc/articles/PMC9490917/ /pubmed/36131313 http://dx.doi.org/10.1186/s12891-022-05826-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Fan, Jingyuan Gu, Fanbin Lv, Lulu Zhang, Zhejin Zhu, Changbing Qi, Jian Wang, Honggang Liu, Xiaolin Yang, Jiantao Zhu, Qingtang Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry |
title | Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry |
title_full | Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry |
title_fullStr | Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry |
title_full_unstemmed | Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry |
title_short | Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry |
title_sort | reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490917/ https://www.ncbi.nlm.nih.gov/pubmed/36131313 http://dx.doi.org/10.1186/s12891-022-05826-4 |
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