Biomechanical analysis of the thoracolumbar spine under physiological loadings: Experimental motion data corridors for validation of finite element models.
Proc Inst Mech Eng H
; 231(10): 975-981, 2017 Oct.
Article
en En
| MEDLINE
| ID: mdl-28707505
Biomechanical studies that involve normal, injured or stabilized human spines are sometimes difficult to perform on large samples due to limited access to cadaveric human spines and biological variability. Finite element models alleviate these limitations due to the possibility of reusing the same model, whereas cadaveric spines can be damaged during testing, or have their mechanicals behaviour modified by fatigue, permanent deformation or structural failure. Finite element models need to be validated with experimental data to make sure that they represent the complex mechanical and physiological behaviour of normal, injured and stabilized spinal segments. The purpose of this study is to characterize the mechanical response of thoracolumbar spine segments with an analytical approach drawn from experimental measurements. A total of 24 normal and fresh cadaveric thoracolumbar spine segments (T11-L3), aged between 53 and 91 years, were tested in pure flexion/extension, lateral bending and axial torsion using a specific experimental setup. Measurements of global and intervertebral angle variations were performed using three-dimensional mark tracking methods. Load/angle curves for each loading were fitted by a logarithmic approach with two coefficients. The coefficients for the functions describing the response of the spinal segments are given and constitute predictive models from experimental data. This work provides data corridors of human thoracolumbar spine motion segments subjected to pure bending in the three physiological planes. These data could be very useful to validate finite element models of the human spine.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Vértebras Torácicas
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Análisis de Elementos Finitos
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Vértebras Lumbares
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Movimiento
Tipo de estudio:
Prognostic_studies
Límite:
Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Año:
2017
Tipo del documento:
Article