Running-specific prosthesis' performance characterization by dynamic finite element approach

Author:

Atai Ali Asghar1,Beiranvand Farshad1ORCID,Jalili Sina2ORCID

Affiliation:

1. School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran

2. Faculty of Mechanical Engineering, Sahand University of Technology, Tabriz, Iran

Abstract

Introduction Composite running-specific prostheses (RSP) are widely used by athletes with lower limb amputations to simulate the spring-like behavior of biological legs. However, the effect of these devices on the biomechanics of athletes with transtibial amputations remains uncertain. Modeling method description: To address this issue, this study proposes a time-dependent finite element model that uses angles and dynamic loads during ground contact to evaluate RSP performance parameters such as stiffness and energy efficiency. The study also examines the impact of running speed and RSP geometry on performance. Numerical Simulation and Model verification: The in-silico characterization approach used in this study takes into account both the intrinsic characteristics of the RSP and the athlete's biomechanics to identify the influence of fundamental geometric variables of the RSP on performance. The model is verified by comparing its results with experimental data. Results and discussion: The study found that as running speed increases, RSP stiffness, vertical ground reaction force (vGRF), and contact time decrease. The force–displacement profiles of RSP are nonlinear, but a linear function can be used to accurately represent their behavior at high sprinting speeds. Using higher RSP reduces energy efficiency and vGRF due to their lower stiffness. J-curve RSP result in higher stiffness, vGRF, and strain energy, while C-curve RSP are associated with longer contact times and higher energy efficiency.

Publisher

Ovid Technologies (Wolters Kluwer Health)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3