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Host Mesh Fitting of a Generic Musculoskeletal Model of the Lower Limbs to Subject-Specific Body Surface Data: A Validation Study.
Applied Bionics and Biomechanics ( IF 1.8 ) Pub Date : 2019-02-17 , DOI: 10.1155/2019/8381351
Katja Oberhofer 1 , Silvio Lorenzetti 1, 2 , Kumar Mithraratne 3
Affiliation  

Challenges remain in accurately capturing the musculoskeletal geometry of individual subjects for clinical and biomechanical gait analysis. The aim of this study was to use and validate the Host Mesh Fitting (HMF) technique for fitting a generic anatomically based musculoskeletal model to 3D body surface data of individual subjects. The HMF technique is based on the free-form idea of deforming geometrically complex structures according to the deformation of a surrounding volumetric mesh. Using the HMF technique, an anatomically based model of the lower limbs of an adult female subject (29 years) was customized to subject-specific skin surface data of five typically developing children (mean age 10.2 years) and six children with Cerebral Palsy (CP) (mean age 9.6 years). The fitted lengths and volumes of six muscle-tendon structures were compared against measures from Magnetic Resonance (MR) images for validation purposes. The HMF technique resulted in accurate approximations of the lower limb shapes of all subjects in both study groups. The average error between the MR data and the fitted muscle-tendon lengths from HMF was in children without CP and in children with CP, respectively. The average error between the MR data and the fitted muscle volumes from HMF was in children without CP and in children with CP, respectively. This study presents a crucial step towards personalized musculoskeletal modelling for gait analysis by demonstrating the feasibility of fitting a generic anatomically based lower limb model to 3D body surface data of children with and without CP using the HMF technique. Additional improvements in the quality of fit are expected to be gained by developing age-matched generic models for different study groups, accounting for subject-specific variations in subcutaneous body fat, as well as considering supplementary data from ultrasound imaging to better capture physiological muscle tissue properties.

中文翻译:

下肢的通用肌肉骨骼模型与主体特定身体表面数据的宿主网格拟合:一项验证研究。

准确地捕获个体受试者的肌肉骨骼几何形状以进行临床和生物力学步态分析仍然存在挑战。这项研究的目的是使用并验证宿主网格拟合(HMF)技术,以将基于通用解剖学的肌肉骨骼模型拟合到单个对象的3D体表数据。HMF技术基于根据周围体积网格的变形使几何复杂结构变形的自由形式思想。使用HMF技术,将成年女性受试者(29岁)下肢的解剖学模型定制为针对五名典型发育中的儿童(平均年龄10.2岁)和六名脑瘫(CP)的受试者特定的皮肤表面数据)(平均年龄9.6岁)。为了验证,将六个肌肉腱结构的拟合长度和体积与磁共振(MR)图像的测量值进行了比较。HMF技术可精确估计两个研究组中所有受试者的下肢形状。MR数据与HMF拟合的肌腱长度之间的平均误差为 在没有CP的儿童中 在患有CP的儿童中。MR数据与HMF拟合的肌肉体积之间的平均误差为 在没有CP的儿童中 在患有CP的儿童中。这项研究通过展示使用HMF技术将具有和不具有CP的儿童的3D体表数据拟合为基于解剖学的通用下肢模型的可行性,为步态分析的个性化肌肉骨骼建模提出了关键的一步。通过为不同的研究组开发年龄匹配的通用模型,考虑皮下脂肪的受试者特定差异以及考虑超声成像的补充数据以更好地捕获生理肌肉组织,有望进一步提高拟合质量属性。
更新日期:2019-02-17
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