基于反向动力学的人体肌肉力预测平台

Inverse dynamics-based platform for human muscle force estimation

背景:目前,国外的商业化软件主要有SIMM、Visual3-D(C-Motion公司)、Anybody(AnybodyTechnology)以及Adams(MSC软件公司),开源软件主要有OpenSim,而国内此类软件的开发比较缓慢。肌肉力预测对于研究神经肌肉协调以及分析运动项目起着非常重要的作用,同时也可以发现病态运动的来源,为康复计划提供科学依据。目的:从全新的角度,完整架构基于反向动力学的人体肌肉力预测平台。方法:详细阐述了基于优化算法的反向动力学人体肌肉力预测平台(MFE-2)的架构过程。该平台可以分析各种运动状态下肌肉力大小,以正常步态为例,分析了该运动过程中上肢主要肌肉的受力情况。结果与结论:通过对一健康人体的正常步态上肢两块典型肌肉(肱三头肌侧头和肱二头肌短头)进行分析,计算结果与相关参考文献基本一致。

BACKGROUND： The foreign business software mainly includes SIMM, Visual 3-D （C-Motion Inc.）, Anybody （Anybody Technology） and Adams （MSC Software Corporation）; open source software mainly includes OpenSim. Domestic development of such software is slow. Muscle force estimation plays an important role in studying neuromuscular coordination and analyzing athletic performance. It can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. OBJECTIVE： From a new perspective, a perfect platform was built based on inverse dynamics for the human muscle force estimation. METHODS： This paper describes the developed process of the platform for muscle force estimation （MFE-2） which based on the optimization algorithm. This platform can analyze muscle force in the state of various human movements. In addition, with a normal gait as an example, muscle force of the major muscles of upper limb was analyzed. RESULTS AND CONCLUSION： Two typical muscles （triceps brachii lateral and biceps brachii short） of a health subject in gait were analyzed, and the calculated result was basically consistent with the relevant references.