Visser Tanya Starret, Ludvig Daniel, Kearney Robert E
Department of Biomedical Engineering, McGill University, Montreal, Canada.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3995-8. doi: 10.1109/IEMBS.2009.5333528.
Previously, we described a time-varying, parallel-cascade system identification algorithm that estimates intrinsic and reflex stiffness dynamics. It uses an iterative technique, in conjunction with established, time-varying, identification methods, to estimate the two pathways from ensembles of input and output realizations having the same time-varying behavior. This paper presents the results of a study that systematically evaluated the performance of the algorithm. Simulations were used to determine the algorithm's ability to track rapid changes in dynamic stiffness, and quantify its performance limits. There was close agreement between the simulated and estimated joint stiffness demonstrating that the algorithm estimates stiffness correctly even when it changes rapidly. However, the algorithm's ability to identify the reflex pathway was shown to depend on the relative contributions of the intrinsic and reflex pathways to the overall torque. As the intrinsic contribution to the output grew it became increasingly difficult to identify the reflex pathway accurately. The quality of the reflex identification greatly improved as the number of realizations in the data ensembles increased. More realizations were needed as the signal-to-noise ratio decreased and the relative contribution of the reflex pathway decreased. For good results, under typical time-varying experimental conditions, between 500 and 800 realizations are required.
此前，我们描述了一种时变的并行级联系统识别算法，该算法可估计内在和反射刚度动态。它使用一种迭代技术，结合既定的时变识别方法，从具有相同随时间变化行为的输入和输出实现集合中估计两条路径。本文展示了一项系统评估该算法性能的研究结果。通过模拟来确定算法跟踪动态刚度快速变化的能力，并量化其性能极限。模拟结果与估计的关节刚度之间有密切的一致性，这表明即使刚度快速变化，该算法也能正确估计刚度。然而，该算法识别反射路径的能力取决于内在和反射路径对总扭矩的相对贡献。随着内在对输出的贡献增加，准确识别反射路径变得越来越困难。随着数据集合中实现次数的增加，反射识别的质量有了很大提高。随着信噪比降低和反射路径的相对贡献减少，需要更多的实现次数。在典型的时变实验条件下，为了获得良好的结果，需要500到800次实现。
