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Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation

BACKGROUND: This study evaluates the conformity of using a computer vision-based posture analysis system as a screening assessment for postural deformity detection in the spine that is easily applicable to clinical practice. METHODS: One hundred forty participants were enrolled for screening of the...

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Autores principales: Kim, Kwang Hyeon, Sohn, Moon-Jun, Park, Chun Gun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9394031/
https://www.ncbi.nlm.nih.gov/pubmed/35996105
http://dx.doi.org/10.1186/s12891-022-05742-7
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author Kim, Kwang Hyeon
Sohn, Moon-Jun
Park, Chun Gun
author_facet Kim, Kwang Hyeon
Sohn, Moon-Jun
Park, Chun Gun
author_sort Kim, Kwang Hyeon
collection PubMed
description BACKGROUND: This study evaluates the conformity of using a computer vision-based posture analysis system as a screening assessment for postural deformity detection in the spine that is easily applicable to clinical practice. METHODS: One hundred forty participants were enrolled for screening of the postural deformation. Factors that determine the presence or absence of spinal deformation, such as shoulder height difference (SHD), pelvic height difference (PHD), and leg length mismatch (LLD), were used as parameters for the clinical decision support system (CDSS) using a commercial computer vision-based posture analysis system. For conformity analysis, the probability of postural deformation provided by CDSS, the Cobb angle, the PHD, and the SHD was compared and analyzed between the system and radiographic parameters. A principal component analysis (PCA) of the CDSS and correlation analysis were conducted. RESULTS: The Cobb angles of the 140 participants ranged from 0° to 61°, with an average of 6.16° ± 8.50°. The postural deformation of CDSS showed 94% conformity correlated with radiographic assessment. The conformity assessment results were more accurate in the participants of postural deformation with normal (0–9°) and mild (10–25°) ranges of scoliosis. The referenced SHD and the SHD of the CDSS showed statistical significance (p < 0.001) on a paired t-test. SHD and PHD for PCA were the predominant factors (PC1 SHD for 79.97%, PC2 PHD for 19.86%). CONCLUSION: The CDSS showed 94% conformity for the screening of postural spinal deformity. The main factors determining diagnostic suitability were two main variables: SHD and PHD. In conclusion, a computer vision-based posture analysis system can be utilized as a safe, efficient, and convenient CDSS for early diagnosis of spinal posture deformation, including scoliosis.
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spelling pubmed-93940312022-08-23 Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation Kim, Kwang Hyeon Sohn, Moon-Jun Park, Chun Gun BMC Musculoskelet Disord Research Article BACKGROUND: This study evaluates the conformity of using a computer vision-based posture analysis system as a screening assessment for postural deformity detection in the spine that is easily applicable to clinical practice. METHODS: One hundred forty participants were enrolled for screening of the postural deformation. Factors that determine the presence or absence of spinal deformation, such as shoulder height difference (SHD), pelvic height difference (PHD), and leg length mismatch (LLD), were used as parameters for the clinical decision support system (CDSS) using a commercial computer vision-based posture analysis system. For conformity analysis, the probability of postural deformation provided by CDSS, the Cobb angle, the PHD, and the SHD was compared and analyzed between the system and radiographic parameters. A principal component analysis (PCA) of the CDSS and correlation analysis were conducted. RESULTS: The Cobb angles of the 140 participants ranged from 0° to 61°, with an average of 6.16° ± 8.50°. The postural deformation of CDSS showed 94% conformity correlated with radiographic assessment. The conformity assessment results were more accurate in the participants of postural deformation with normal (0–9°) and mild (10–25°) ranges of scoliosis. The referenced SHD and the SHD of the CDSS showed statistical significance (p < 0.001) on a paired t-test. SHD and PHD for PCA were the predominant factors (PC1 SHD for 79.97%, PC2 PHD for 19.86%). CONCLUSION: The CDSS showed 94% conformity for the screening of postural spinal deformity. The main factors determining diagnostic suitability were two main variables: SHD and PHD. In conclusion, a computer vision-based posture analysis system can be utilized as a safe, efficient, and convenient CDSS for early diagnosis of spinal posture deformation, including scoliosis. BioMed Central 2022-08-22 /pmc/articles/PMC9394031/ /pubmed/35996105 http://dx.doi.org/10.1186/s12891-022-05742-7 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 Article
Kim, Kwang Hyeon
Sohn, Moon-Jun
Park, Chun Gun
Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation
title Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation
title_full Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation
title_fullStr Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation
title_full_unstemmed Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation
title_short Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation
title_sort conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9394031/
https://www.ncbi.nlm.nih.gov/pubmed/35996105
http://dx.doi.org/10.1186/s12891-022-05742-7
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