A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation

In population-oriented ergonomics product design and musculoskeletal kinetics analysis, digital spine models of different shape, pose and material property are in great demand. The purpose of this study was to construct a parameterized finite element spine model with adjustable spine shape and mater...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Xiaobang Sun, Hongkai Wang, Weiying Wang, Nannan Li, Timo Hamalainen, Tapani Ristaniemi, Changjian Liu
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Spine modelling biomechanical simulation statistical shape modelling finite element analysis population anatomy modelling Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/74c46ba4dc0647d3b4cbbc48fea27347
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:74c46ba4dc0647d3b4cbbc48fea27347
record_format	dspace
spelling	oai:doaj.org-article:74c46ba4dc0647d3b4cbbc48fea273472021-12-01T00:01:27ZA Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation2169-353610.1109/ACCESS.2021.3129097https://doaj.org/article/74c46ba4dc0647d3b4cbbc48fea273472021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9618930/https://doaj.org/toc/2169-3536In population-oriented ergonomics product design and musculoskeletal kinetics analysis, digital spine models of different shape, pose and material property are in great demand. The purpose of this study was to construct a parameterized finite element spine model with adjustable spine shape and material property. We used statistical shape model approach to learn inter-subject shape distribution from 65 CT images of training subjects. Second order polynomial regression was used to model the age-dependent changes in vertebral material property derived from spatially aligned CT images. Finally, a parametric spine generator was developed to create finite element instances of different shapes and material properties. For quantitative analysis, the generalization ability to emulate spine shapes of different people was evaluated by fitting into 17 test CT images. The median fitting accuracy was 0.8 for Dice coefficient and 0.43 mm for average surface distance. The age-dependent bone density regression curve was also proved to well agree with large population statistics data. Finite element simulation was performed to compare how shape parameters influenced the biomechanics distribution of spine. The proposed parametric finite element whole spine model will assist the design process of new devices and biomechanical simulation towards a wide range of population.Xiaobang SunHongkai WangWeiying WangNannan LiTimo HamalainenTapani RistaniemiChangjian LiuIEEEarticleSpine modellingbiomechanical simulationstatistical shape modellingfinite element analysispopulation anatomy modellingElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 155805-155814 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Spine modelling biomechanical simulation statistical shape modelling finite element analysis population anatomy modelling Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Spine modelling biomechanical simulation statistical shape modelling finite element analysis population anatomy modelling Electrical engineering. Electronics. Nuclear engineering TK1-9971 Xiaobang Sun Hongkai Wang Weiying Wang Nannan Li Timo Hamalainen Tapani Ristaniemi Changjian Liu A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation
description	In population-oriented ergonomics product design and musculoskeletal kinetics analysis, digital spine models of different shape, pose and material property are in great demand. The purpose of this study was to construct a parameterized finite element spine model with adjustable spine shape and material property. We used statistical shape model approach to learn inter-subject shape distribution from 65 CT images of training subjects. Second order polynomial regression was used to model the age-dependent changes in vertebral material property derived from spatially aligned CT images. Finally, a parametric spine generator was developed to create finite element instances of different shapes and material properties. For quantitative analysis, the generalization ability to emulate spine shapes of different people was evaluated by fitting into 17 test CT images. The median fitting accuracy was 0.8 for Dice coefficient and 0.43 mm for average surface distance. The age-dependent bone density regression curve was also proved to well agree with large population statistics data. Finite element simulation was performed to compare how shape parameters influenced the biomechanics distribution of spine. The proposed parametric finite element whole spine model will assist the design process of new devices and biomechanical simulation towards a wide range of population.
format	article
author	Xiaobang Sun Hongkai Wang Weiying Wang Nannan Li Timo Hamalainen Tapani Ristaniemi Changjian Liu
author_facet	Xiaobang Sun Hongkai Wang Weiying Wang Nannan Li Timo Hamalainen Tapani Ristaniemi Changjian Liu
author_sort	Xiaobang Sun
title	A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation
title_short	A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation
title_full	A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation
title_fullStr	A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation
title_full_unstemmed	A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation
title_sort	statistical model of spine shape and material for population-oriented biomechanical simulation
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/74c46ba4dc0647d3b4cbbc48fea27347
work_keys_str_mv	AT xiaobangsun astatisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT hongkaiwang astatisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT weiyingwang astatisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT nannanli astatisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT timohamalainen astatisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT tapaniristaniemi astatisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT changjianliu astatisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT xiaobangsun statisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT hongkaiwang statisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT weiyingwang statisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT nannanli statisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT timohamalainen statisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT tapaniristaniemi statisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation AT changjianliu statisticalmodelofspineshapeandmaterialforpopulationorientedbiomechanicalsimulation
_version_	1718406148179099648

A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation

Ejemplares similares