Determining residual reduction algorithm kinematic tracking weights for a sidestep cut via numerical optimization
Determining residual reduction algorithm kinematic tracking weights for a sidestep cut via numerical optimization
复制标题
通过数值优化确定侧步切割的残余减少算法运动跟踪权重
DOI：
10.1080/10255842.2016.1183123
复制
发表时间：
2016
影响因子：
1.6
通讯作者：
S. Ringleb
中科院分区：
文献类型：
--
作者：
M. Samaan;Joshua T. Weinhandl;S. Bawab;S. Ringleb
摘要肌肉骨骼模型可以通过使用体内运动学和地面反作用力（GRF）数据作为输入来确定动态机动过程中的各种参数。实验和模型标记数据之间的差异以及应用于这些肌肉骨骼模型的GRF中的不一致性可能不会产生准确的模拟。因此，将残余力和力矩应用于这些模型，以减少这些差异。数值优化技术可用于确定肌肉骨骼模型的每个自由度的最佳跟踪权重，以减少实验和模型标记数据之间的差异以及残余力和力矩。在这项研究中，粒子群优化（PSO）和单纯形模拟退火（SIMPSA）算法被用来确定最佳的跟踪权重的模拟台阶切割。粒子群算法和SIMPSA算法能够产生的模型运动学是在1.4°的实验运动学与残余力和力矩小于10 N和18 Nm，分别。与SIMPSA算法相比，PSO算法能够更紧密地复制实验运动学数据，并为台阶切割产生更动态一致的运动学数据。未来的研究应该使用外部优化程序来确定动态一致的运动学数据，并报告这些肌肉骨骼模拟的实验和模型数据之间的差异。
Abstract Musculoskeletal modeling allows for the determination of various parameters during dynamic maneuvers by using in vivo kinematic and ground reaction force (GRF) data as inputs. Differences between experimental and model marker data and inconsistencies in the GRFs applied to these musculoskeletal models may not produce accurate simulations. Therefore, residual forces and moments are applied to these models in order to reduce these differences. Numerical optimization techniques can be used to determine optimal tracking weights of each degree of freedom of a musculoskeletal model in order to reduce differences between the experimental and model marker data as well as residual forces and moments. In this study, the particle swarm optimization (PSO) and simplex simulated annealing (SIMPSA) algorithms were used to determine optimal tracking weights for the simulation of a sidestep cut. The PSO and SIMPSA algorithms were able to produce model kinematics that were within 1.4° of experimental kinematics with residual forces and moments of less than 10 N and 18 Nm, respectively. The PSO algorithm was able to replicate the experimental kinematic data more closely and produce more dynamically consistent kinematic data for a sidestep cut compared to the SIMPSA algorithm. Future studies should use external optimization routines to determine dynamically consistent kinematic data and report the differences between experimental and model data for these musculoskeletal simulations.
登录
查看更多内容
跑步过程中肌肉对推进和支撑的贡献。
影响因子：
2.4
作者：
Hamner, Samuel R.;Seth, Ajay;Delp, Scott L.
通讯作者：
Delp, Scott L.
DOI：
10.1115/1.2834295
发表时间：
1998-02-01
影响因子：
1.7
作者：
Kuo, AD
通讯作者：
Kuo, AD
影响因子：
2.4
作者：
YAMAGUCHI, GT;ZAJAC, FE
通讯作者：
ZAJAC, FE
影响因子：
2.4
作者：
Anderson, FC;Pandy, MG
通讯作者：
Pandy, MG
用于步态正向动态模拟的动态一致运动学和动力学的最佳估计。
DOI：
10.1115/1.3005148
发表时间：
2009
期刊：
Journal of biomechanical engineering
影响因子：
--
作者：
Remy,CDavid;Thelen,DarrylG
通讯作者：
Thelen,DarrylG