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Load-displacement relationships of spinal motion segments are crucial factors in characterizing the stiffness of scoliotic spine models to mimic the spine responses to loads. Although nonlinear approach to approximation of the relationships can be superior to linear ones, little mention has been made to deriving personalized nonlinear load-displacement relationships in previous studies. A method is developed for nonlinear approximation of load-displacement relationships of spinal motion segments to assist characterizing in vivo the stiffness of spine models. We propose approximation by tangent functions and focus on rotational displacements in lateral direction. The tangent functions are characterized using lateral bending test. A multi-body model was characterized to 18 patients and utilized to simulate four spine positions; right bending, left bending, neutral, and traction. The same was done using linear functions to assess the performance of the proposed tangent function in comparison with the linear function. Root-mean-square error (RMSE) of the displacements estimated by the tangent functions was 44 % smaller than the linear functions. This shows the ability of our tangent function in approximation of the relationships for a range of infinitesimal to large displacements involved in the spine movement to the four positions. In addition, the models based on the tangent functions yielded 67, 55, and 39 % smaller RMSEs of Ferguson angles, locations of vertebrae, and orientations of vertebrae, respectively, implying better estimates of spine responses to loads. Overall, it can be concluded that our method for approximating load-displacement relationships of spinal motion segments can offer good estimates of scoliotic spine stiffness.

This paper studies how biomechanical multibody models of scoliosis can neglect the changes of spinal length and yet be accurate in reconstructing spinal columns. As these models with fixed length comprise rigid links interconnected by rotary joints, they resemble polygonal chains that approximate spine curves with a finite number of line segments. In mathematics, using more segments with shorter lengths can result in more accurate curve approximations. This raises the question of whether more accurate spine curve approximations by increasing the number of links/joints can yield more accurate spinal column reconstructions. For this, the accuracy of spine curve approximation was improved consistently by increasing the number of links/joints, and its effects on the accuracy of spinal column reconstruction were assessed. Positive correlation was found between the accuracy of spine reconstruction and curve approximation. It was shown that while increasing the accuracy of curve approximations, the representation of scoliosis concavity and its side-to-side deviations were improved. Moreover, reconstruction errors of the spine regions separated by the inflection vertebrae had minimal impacts on each other. Overall, multibody scoliosis models with fixed spinal lengths can benefit from the extra rotational joints that contribute toward the accuracy of spine curve approximation. The outcome of this study leads to concurrent accuracy improvement and simplification of multibody models; joint-link configurations can be independently defined for the regions separated by the inflection vertebrae, enabling local optimization of the models for higher accuracy without unnecessary added complexity to the whole model. [ABSTRACT FROM AUTHOR]