Statistical Shape Analysis of Human Bodies

Morphological analysis of the human body is crucial for various applications in ergonomics and product design, with significant economic and commercial implications. This paper presents a novel exploration of statistical methods for the analysis of human body shapes based on 3D landmark data. It foc...

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Detalles Bibliográficos
Autores: Valero, J, Ibáñez, MV, Simó, A
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
Repositorio:r-FISABIO. Repositorio Institucional de Producción Científica
OAI Identifier:oai:dnet:r-fisabio___::a8aece0466de0d597e099e36d1a15930
Acceso en línea:https://fisabio.portalinvestigacion.com/publicaciones/21022
Access Level:acceso abierto
Palabra clave:anthropometry
principal component analysis
Riemannian manifold
statistical shape analysis
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spelling Statistical Shape Analysis of Human BodiesValero, JIbáñez, MVSimó, Aanthropometryprincipal component analysisRiemannian manifoldstatistical shape analysisMorphological analysis of the human body is crucial for various applications in ergonomics and product design, with significant economic and commercial implications. This paper presents a novel exploration of statistical methods for the analysis of human body shapes based on 3D landmark data. It focuses on the application of well-established statistical methods within the framework of Kendall's 3D shape space. It is well known that Kendall's 3D shape space has non-constant curvature at all points. A key contribution of this study is the detailed examination of the curvature of Kendall's space at points corresponding to human body shapes, highlighting its implications for posterior statistical analysis. A study of the distances in the dataset is also carried out. From this point, we also compare the performance of intrinsic (Riemannian) methods and Euclidean approximations for mean shape estimation, group difference identification, and dimensionality reduction, providing a comprehensive assessment of their respective strengths and limitations in these contexts. These findings aim to improve the statistical understanding of body morphology and provide valuable guidance for applications in fields such as product design and ergonomics.WILEY2025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://fisabio.portalinvestigacion.com/publicaciones/21022Statistical Analysis and Data Mining-An Asa Data Science JournalISSN: 19321864ISSNe: 19321872reponame:r-FISABIO. Repositorio Institucional de Producción Científicainstname:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)Inglésinfo:eu-repo/semantics/openAccessoai:dnet:r-fisabio___::a8aece0466de0d597e099e36d1a159302026-06-11T12:45:17Z
dc.title.none.fl_str_mv Statistical Shape Analysis of Human Bodies
title Statistical Shape Analysis of Human Bodies
spellingShingle Statistical Shape Analysis of Human Bodies
Valero, J
anthropometry
principal component analysis
Riemannian manifold
statistical shape analysis
title_short Statistical Shape Analysis of Human Bodies
title_full Statistical Shape Analysis of Human Bodies
title_fullStr Statistical Shape Analysis of Human Bodies
title_full_unstemmed Statistical Shape Analysis of Human Bodies
title_sort Statistical Shape Analysis of Human Bodies
dc.creator.none.fl_str_mv Valero, J
Ibáñez, MV
Simó, A
author Valero, J
author_facet Valero, J
Ibáñez, MV
Simó, A
author_role author
author2 Ibáñez, MV
Simó, A
author2_role author
author
dc.subject.none.fl_str_mv anthropometry
principal component analysis
Riemannian manifold
statistical shape analysis
topic anthropometry
principal component analysis
Riemannian manifold
statistical shape analysis
description Morphological analysis of the human body is crucial for various applications in ergonomics and product design, with significant economic and commercial implications. This paper presents a novel exploration of statistical methods for the analysis of human body shapes based on 3D landmark data. It focuses on the application of well-established statistical methods within the framework of Kendall's 3D shape space. It is well known that Kendall's 3D shape space has non-constant curvature at all points. A key contribution of this study is the detailed examination of the curvature of Kendall's space at points corresponding to human body shapes, highlighting its implications for posterior statistical analysis. A study of the distances in the dataset is also carried out. From this point, we also compare the performance of intrinsic (Riemannian) methods and Euclidean approximations for mean shape estimation, group difference identification, and dimensionality reduction, providing a comprehensive assessment of their respective strengths and limitations in these contexts. These findings aim to improve the statistical understanding of body morphology and provide valuable guidance for applications in fields such as product design and ergonomics.
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://fisabio.portalinvestigacion.com/publicaciones/21022
url https://fisabio.portalinvestigacion.com/publicaciones/21022
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv WILEY
publisher.none.fl_str_mv WILEY
dc.source.none.fl_str_mv Statistical Analysis and Data Mining-An Asa Data Science Journal
ISSN: 19321864
ISSNe: 19321872
reponame:r-FISABIO. Repositorio Institucional de Producción Científica
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instname_str Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
reponame_str r-FISABIO. Repositorio Institucional de Producción Científica
collection r-FISABIO. Repositorio Institucional de Producción Científica
repository.name.fl_str_mv
repository.mail.fl_str_mv
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