Lower Cervical Spine Motion Segment Computational Model Validation: Kinematic and Kinetic Response for Quasi-Static and Dynamic Loading

运动学 计算机科学 有限元法 旋转(数学) 计算模型 实验数据 模拟 航程(航空) 结构工程 生物力学 数学 工程类 统计 人工智能 物理 经典力学 热力学 航空航天工程
作者
J. Barker,Duane S. Cronin,Roger W. Nightingale
出处
期刊:Journal of biomechanical engineering [ASM International]
卷期号:139 (6) 被引量:36
标识
DOI:10.1115/1.4036464
摘要

Advanced computational human body models (HBM) enabling enhanced safety require verification and validation at different levels or scales. Specifically, the motion segments, which are the building blocks of a detailed neck model, must be validated with representative experimental data to have confidence in segment and, ultimately, full neck model response. In this study, we introduce detailed finite element motion segment models and assess the models for quasi-static and dynamic loading scenarios. Finite element segment models at all levels in the lower human cervical spine were developed from scans of a 26-yr old male subject. Material properties were derived from the in vitro experimental data. The segment models were simulated in quasi-static loading in flexion, extension, lateral bending and axial rotation, and at dynamic rates in flexion and extension in comparison to previous experimental studies and new dynamic experimental data introduced in this study. Single-valued experimental data did not provide adequate information to assess the model biofidelity, while application of traditional corridor methods highlighted that data sets with higher variability could lead to an incorrect conclusion of improved model biofidelity. Data sets with continuous or multiple moment–rotation measurements enabled the use of cross-correlation for an objective assessment of the model and highlighted the importance of assessing all motion segments of the lower cervical spine to evaluate the model biofidelity. The presented new segment models of the lower cervical spine, assessed for range of motion and dynamic/traumatic loading scenarios, provide a foundation to construct a biofidelic model of the spine and neck, which can be used to understand and mitigate injury for improved human safety in the future.
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