Abstract
Computational modeling and simulation studies involving human spine using finite element methods typically encompass fixed geometry and material properties. The accuracy and reliability of the response obtained from these simulations are largely influenced by the input data from human spine. Input data uncertainties associated with natural variations in geometry and material characteristics of the human spine cause response to be imprecise. In addition if human is a pediatric human, growth rate uncertainties influence the predictions and their validations against experimental findings. The end result is the uncertainties in computationally predicted response. Some prediction uncertainties can be reduced by additional data collection and characterization. This paper presents a unique in-vivo noninvasive method and characterizes geometry and growth rate of human spine. The results will serve useful in reducing prediction uncertainties in finite element simulations of human spine. This study is the first extensive study of the pediatric spinal structure dimensions to include such a large variety of bony structures for this particular age group.
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Doughty, E.S., Sarigul-Klijn, N. (2017). Towards Reducing Prediction Uncertainties in Human Spine Finite Element Response: In-Vivo Characterization of Growth and Spine Morphology. In: Barthorpe, R., Platz, R., Lopez, I., Moaveni, B., Papadimitriou, C. (eds) Model Validation and Uncertainty Quantification, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-54858-6_32
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DOI: https://doi.org/10.1007/978-3-319-54858-6_32
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