穿着最小、最大和传统鞋类跑步对胫骨应力性骨折概率的影响:使用有限元分析和概率分析进行研究

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Computation Pub Date : 2023-12-06 DOI:10.3390/computation11120248
Jonathan K Sinclair, P. Taylor
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引用次数: 0

摘要

本研究采用有限元和概率分析的方法研究了最小跑鞋、最大跑鞋和常规跑鞋对胫骨应变和应力骨折概率的影响。目前的调查调查了15名男性在三种跑鞋条件下跑步(最小、最大和常规)。在以4.0 m/s的速度进行地上跑步时,使用8个摄像头的运动捕捉系统收集了运动学数据,并使用测力板收集了地面反作用力。通过有限元建模量化胫骨应变,通过概率建模计算100天的应力断裂概率。第90百分位胫骨应变在最小鞋履(4681.13 με) (p < 0.001)和常规鞋履(4498.84 με) (p = 0.007)中显著高于最大鞋履(4069.65 με)。此外,最小鞋履的胫骨应力骨折概率显著高于最大鞋履(0.15)(p = 0.047)(0.22)。这项调查的观察结果表明,与最小的跑鞋相比,最大的跑鞋似乎可以有效地降低跑步者发生胫骨应力性骨折的可能性。
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Effects of Running in Minimal, Maximal and Conventional Footwear on Tibial Stress Fracture Probability: An Examination Using Finite Element and Probabilistic Analyses
This study examined the effects of minimal, maximal and conventional running footwear on tibial strains and stress fracture probability using finite element and probabilistic analyses. The current investigation examined fifteen males running in three footwear conditions (minimal, maximal and conventional). Kinematic data were collected during overground running at 4.0 m/s using an eight-camera motion-capture system and ground reaction forces using a force plate. Tibial strains were quantified using finite element modelling and stress fracture probability calculated via probabilistic modelling over 100 days of running. Ninetieth percentile tibial strains were significantly greater in minimal (4681.13 με) (p < 0.001) and conventional (4498.84 με) (p = 0.007) footwear compared to maximal (4069.65 με). Furthermore, tibial stress fracture probability was significantly greater in minimal footwear (0.22) (p = 0.047) compared to maximal (0.15). The observations from this investigation show that compared to minimal footwear, maximal running shoes appear to be effective in attenuating runners’ likelihood of developing a tibial stress fracture.
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来源期刊
Computation
Computation Mathematics-Applied Mathematics
CiteScore
3.50
自引率
4.50%
发文量
201
审稿时长
8 weeks
期刊介绍: Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.
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