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首页> 外文期刊>Journal of biomechanical engineering. >Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review
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Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review

机译：估计上肢和下肢人关节运动学估计的多体运动学优化：系统化方法综述

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摘要

Multibody kinematics optimization (MKO) aims to reduce soft tissue artefact (STA) and is a key step in musculoskeletal modeling. The objective of this review was to identify the numerical methods, their validation and performance for the estimation of the human joint kinematics using MKO. Seventy-four papers were extracted from a systematized search in five databases and cross-referencing. Model-derived kinematics were obtained using either constrained optimization or Kalman filtering to minimize the difference between measured (i.e., by skin markers, electromagnetic or inertial sensors) and model-derived positions and/or orientations. While hinge, universal, and spherical joints prevail, advanced models (e.g., parallel and four-bar mechanisms, elastic joint) have been introduced, mainly for the knee and shoulder joints. Models and methods were evaluated using: (i) simulated data based, however, on oversimplified STA and joint models; (ii) reconstruction residual errors, ranging from 4mm to 40 mm; (iii) sensitivity analyses which highlighted the effect (up to 36 deg and 12 mm) of model geometrical parameters, joint models, and computational methods; (iv) comparison with other approaches (i. e., single body kinematics optimization and nonoptimized kinematics); (v) repeatability studies that showed low intra-and inter-observer variability; and (vi) validation against ground-truth bone kinematics with errors between 1 deg and 22 deg for tibiofemoral rotations and between 3 deg and 10 deg for glenohumeral rotations). Moreover, MKO was applied to various movements (e.g., walking, running, arm elevation). Additional validations, especially for the upper limb, should be undertaken and we recommend a more systematic approach for the evaluation of MKO. In addition, further model development, scaling, and personalization methods are required to better estimate the secondary degrees-of-freedom (DoF).
机译：多体运动学优化（MKO）旨在减少软组织艺术品（STA），是肌肉骨骼建模的关键步骤。本综述的目的是确定使用MKO估计人类关节运动学的数值方法，验证和性能。从5个数据库中的系统化搜索中提取了七十四篇论文并交叉引用。使用受约束的优化或卡尔曼滤波获得模型衍生的运动学，以最小化测量（即，通过皮肤标记，电磁或惯性传感器）和模型衍生位置和/或方向之间的差异。虽然铰链，通用和球形接头占上风，但是先进的模型（例如，平行和四条机构，弹性接头），主要用于膝盖和肩部接头。使用：（i）基于超简化的STA和联合模型的模拟数据评估模型和方法; （ii）重建剩余误差，范围为4mm至40 mm; （iii）突出显示模型几何参数，联合模型和计算方法的效果（高达36°和12 mm）的敏感性分析; （iv）与其他方法（I.），单身运动学优化和非优化的运动学比较）; （v）显示出低于内或观察者间变异性低的重复性研究; （vi）针对地面真理骨骼运动学的验证，术语在1°和22°之间的误差和胫骨旋转之间的误差和胶质形状旋转的3°和10°之间）。此外，MKO被应用于各种运动（例如，行走，跑步，手臂海拔）。应进行额外的验证，特别是对于上肢，应该进行更系统的评估方法，以便评估MKO。此外，还需要进一步的模型开发，缩放和个性化方法来更好地估计二次自由度（DOF）。

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