Zhang X, Chaffin D
Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, 61801, USA.
Ergonomics. 2000 Sep;43(9):1314-30. doi: 10.1080/001401300421761.
A three-dimensional dynamic posture prediction model for simulating in-vehicle seated reaching movements is presented. The model employs a four-segment 7-degrees-of-freedom linkage structure to represent the torso, clavicle and right upper extremity. It relies on an optimization-based differential inverse kinematics approach to estimate a set of four weighting parameters that quantify a time-constant, inter-segment motion apportionment strategy. In the development phase, 100 seated reaching movements performed by 10 subjects towards five typical in-vehicle targets were modelled, resulting in 100 sets of weighting parameters. Statistical analysis was then conducted to relate these parameters to target and individual attributes. In the validation phase, the generalized model, with parameter values statistically synthesized, was applied to novel data sets containing 700 different reaching movements (towards different targets and/or by different subjects). The results demonstrated the model's ability to generate close representations in prediction: the overall mean time-averaged error in joint angle was 5.2 degrees, and the median was 4.7 degrees, excluding reaches towards two extreme targets (for which modelling errors were excessive). The model's general success in prediction and its unique characteristics led to implications with regard to the performance and underlying control strategies of human reaching movements.
提出了一种用于模拟车内坐姿够取动作的三维动态姿势预测模型。该模型采用四段七自由度连杆结构来表示躯干、锁骨和右上臂。它依靠基于优化的微分逆运动学方法来估计一组四个加权参数,这些参数量化了一种时间常数、节段间运动分配策略。在开发阶段,对10名受试者向五个典型车内目标进行的100次坐姿够取动作进行建模,得到100组加权参数。然后进行统计分析,将这些参数与目标和个体属性相关联。在验证阶段,将具有统计合成参数值的广义模型应用于包含700种不同够取动作(针对不同目标和/或由不同受试者完成)的新数据集。结果表明该模型在预测中能够生成接近的表示:关节角度的总体平均时间平均误差为5.2度,中位数为4.7度,不包括向两个极端目标的够取动作(对于这两个目标建模误差过大)。该模型在预测方面的总体成功及其独特特性对人类够取动作的性能和潜在控制策略具有启示意义。