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A finite element model for predicting the biomechanical behaviour of the human lumbar spine

  • The aim of this study was to develop a biomechanically validated finite element model to predict the biomechanical behaviour of the human lumbar spine in compression. For validation of the finite element model, an in vitro study was performed: Twelve human lumbar cadaveric spinal segments (six segments L2/3 and six segments L4/5) were loaded in axial compression using 600 N in the intact stateThe aim of this study was to develop a biomechanically validated finite element model to predict the biomechanical behaviour of the human lumbar spine in compression. For validation of the finite element model, an in vitro study was performed: Twelve human lumbar cadaveric spinal segments (six segments L2/3 and six segments L4/5) were loaded in axial compression using 600 N in the intact state and following surgical treatment using two different internal stabilisation devices. Range of motion was measured and used to calculate stiffness. A finite element model of a human spinal segment L3/4 was loaded with the same force in intact and surgically altered state, corresponding to the situation of biomechanical in vitro study. The results of the cadaver biomechanical and finite element analysis were compared. As they were close together, the finite element model was used to predict: (1) load-sharing within human lumbar spine in compression, (2) load-sharing within osteoporotic human lumbar spine in compression and (3) the stabilising potential of the different spinal implants with respect to bone mineral density. A finite element model as described here may be used to predict the biomechanical behaviour of the spine. Moreover, the influence of different spinal stabilisation systems may be predicted.show moreshow less

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Metadaten
Author:Tobias Pitzen, Fred Geisler, Dieter Matthias, Hans Müller-Storz, Dragos Barbier, Wolf-Ingo Steudel
Publisher:Elsevier
Year of Publication:2002
Language:English
GND Keyword:Biomechanik; Finite-Elemente-Methode; Prognose
Parent Title (English):Control Engineering Practice
Volume:10
Issue:1
ISSN:1873-6939
First Page:83
Last Page:90
Document Type:Article (reviewed)
Open Access:Frei zugänglich
Institutes:Bibliografie
Release Date:2019/10/17
Licence (German):License LogoEs gilt das UrhG
DOI:https://doi.org/10.1016/S0967-0661(01)00129-0