Research>Dynamic Strength and Fatigue Modeling
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Dynamic Strength and Fatigue Modeling

The Fundamentals: Rather than modeling individual muscles, we work with joints.   Our goal is to determine a surface for each joint as maximum joint torque versus angular velocity and joint angle. 

Digital models provide information on how humans might perform a task; however, it is another issue for a digital human model to provide feedback about their ability to realistically perform a task. In other words, they cannot tell us how "difficult" a task "felt". In approaching the issue of human strength and fatigue, it was decided to break down a “whole-body fatigue” concept into two parts; muscle strength and aerobic energy consumption. Our current work is focused on determining a relationship between human muscle strength capability and the ability to perform given tasks which will then be implemented in a digital human model. To study this relationship, literature pertaining to human strength, more specifically, the torque-velocity relationship and fatigue was reviewed. A study is in progress to explore whether a connection between anthropometric characteristics and strength capability exists. To perform this study, a population of healthy adults will be tested on a Biodex isokinetic dynamometer to determine their maximum torque outputs at various angular positions and angular velocities.  After experimentally measuring joint torque at several isometric positions and isokinetic angular velocities, a 3D plot of torque, position and velocity will be developed. This 3D plot will not only allow us to evaluate torque based on changing angular velocity but also on changing moment arm and fiber length with varying joint angle. By collecting more detailed anthropometrical measurements, we will compare a subject's physical characteristics with their strength data which may help explain variability seen in previous studies reviewed. While there is much torque-velocity data found in literature, few studies include all the variables of interest in terms of digital human modeling and have several methodological limitations. These include lack of an isometric data point, too few data points, reports of group mean results only, and lack of detailed anthropometrical measurements (Farthing & Chilibeck, 2003; Weir, et al, 1996). The overall goal of this study is to obtain these variables and attempt to determine their relationships relative to each other. Implementing this information in a digital human model will enable us to give the most realistic simulations by limiting it to reasonable human strength capabilities and providing a measure of “perceived difficulty” by the digital human. In turn this will ultimately enable more accurate and less expensive testing of product safety, maintainability, and serviceability.

 

 

 

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