A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation
Sun, X., Wang, H., Wang, W., Li, N., Hämäläinen, T., Ristaniemi, T., & Liu, C. (2021). A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation. IEEE Access, 9, 155805-155814. https://doi.org/10.1109/access.2021.3129097
Published inIEEE Access
DisciplineTietotekniikkaOhjelmisto- ja tietoliikennetekniikkaSecure Communications Engineering and Signal ProcessingMathematical Information TechnologySoftware and Communications EngineeringSecure Communications Engineering and Signal Processing
© 2021 the Authors
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 variations 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. ...
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Publication in research information system
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Additional information about fundingGeneral program of National Natural Science Fund of China (Grant Number: 61971089, 61971445 and 81971693) National Key Research and Development Program (Grant Number: 2020YFB1711501 and 2020YFB1711503) Fundamental Research Funds for the Central Universities (Grant Number: DUT19JC01 and DUT20YG122)
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