Knee Stability under Time-Varying Multiple-Muscle Loads

描述（由申请人提供）：量化膝关节稳定性力学，特别是在生理负荷条件下（即时变多肌肉负荷），对于了解膝关节韧带失效时多肌肉的广泛作用至关重要。本研究的重点是建立一个计算模型，通过一个复杂的尸体-机器人装置来验证膝关节韧带张力、胫骨运动和节间力是如何受到时间变化的肌肉负荷在同步动态姿势下对ACL受损和未受损膝盖的影响的。长期目标是进一步了解功能性acl缺陷（ACL-D）受试者减轻相关韧带劳损的方式和程度。对尸体韧带应变的定量测量将作为量化膝关节稳定性的更大努力的一部分。协同实验和计算方法将被实施，并导致(1)模拟体内膝关节负荷条件的实验设备和程序的发展，以及(2)通过实验数据验证的图形计算膝关节模型。这些研究结合了来自人体运动研究、机器人尸体实验装置和计算模型的现有数据。先前的人体运动研究将为实验和计算方法提供数据。这两种方法都将量化韧带应变和关节稳定性参数。机器人尸体和计算模型之间的统计比较将用于评估和完善模型。一旦验证，该模型可用于研究其他膝关节不稳定性参数和ACL-D肌肉恢复。本建议概述了建立定量模型评估韧带劳损的第一步，特别是与前交叉韧带损伤和修改肌肉恢复策略以保持完全功能相关的受试者。对这种机制的理解可以导致非手术物理治疗干预，从而减少手术侵入的需要。

DESCRIPTION (provided by applicant): Quantifying knee-stability mechanics, especially under physiological loading conditions (i.e., time-varying multiple-muscle loads), is critical to understanding the broader aspects of multiple muscle contributions in light of knee ligament failure. The focus of this research is to develop a computational model verified by a sophisticated cadaver-robotic setup to investigate the how knee ligament strain, tibial movement, and intersegmental forces are affected by time-varying muscle loads in synchronous dynamic postures in both ACL impaired and un-impaired knees. The long-term aim is to gain further understanding of the means and extent to which functional ACL-Deficient (ACL-D) subjects reduce associated ligament strain. Quantitative measurements on cadaver ligament strain will be performed as part of the larger effort to quantify knee stability. Synergistic experimental and computational methods will be implemented and lead to the development of (1) an experimental apparatus and procedure to mimic in-vivo knee loading conditions, and (2) a graphical-computational knee model verified by experimental data. These incorporate existing data from human-motion studies, a robot-cadaver experimental set-up, and computational modeling. Previous human-motion studies will provide the data for both the experimental and computational approaches. Both approaches will quantify ligament strain and joint stability parameters. Statistical comparisons between the robot-cadaver and computational model will be used to assess and refine the model. Once verified, the model can be used to investigate other knee [instability parameters and ACL-D muscle recruitment. This proposal outlines the first steps toward establishing a quantitative model for assessment of ligament strain, especially as it relates to subjects with ACL injuries and who have modified their muscle recruitment strategy to remain fully functional. Understanding of such mechanisms could lead to non-surgical physical therapy interventions and thus reduce the need for a surgical intrusion.