Methods for Experimental Identification of Nonlinear Dynamic Systems of Unknown Form and Order With Application to Human Gait

这项研究旨在开发新的方法来询问人类步态的实验测量，以便更好地了解神经肌肉系统在这一重要过程中的功能。本文将研究一种新的非线性系统识别策略，该策略利用系统模型，该模型适用于与标称周期运动（或平均步幅周期）的小偏差。利用线性时间周期系统理论，建立了一种频域输出系统识别方法来表征系统在周期轨迹上的运动，并将其用于寻找非线性系统的数学模型。一个基于视频的动作捕捉系统将被用来记录几个受试者在仪器跑步机上行走时的动作，这些测量结果将被用来识别他们步态过程中神经肌肉功能的简化模型。然后，该模型将被整合到计算肌肉控制前向动力学算法中，以获得对单个肌肉的作用和步态中神经肌肉系统功能的额外见解。这项工作有望改善步态障碍的治疗方法，可能使美国成千上万目前患有这些疾病的人受益。常见的步态障碍可能源于出生缺陷，疾病的残余影响，如小儿麻痹症，或来自体育活动，事故或军事战斗中持续的伤害，尽管已经提出了许多治疗步态障碍的方法，但目前很难预测治疗的有效性。这项工作有望增加我们对步态的理解，以便更可靠地选择适当的治疗方法。此外，在这项工作中使用的框架是通用的，因此所开发的方法也可以用于研究其他非线性系统，如车辆，风力涡轮机，机械等。将根据这项研究的结果创建一个短期课程，并将用于与广大受众分享这些新方法。

This research seeks to develop new methods for interrogating experimental measurements of human gait in order to better understand how the neuromuscular system functions during this important process. A new nonlinear system identification strategy will be studied that utilizes a model for the system that is appropriate for small deviations from a nominal periodic motion (or average stride cycle). A frequency-domain output-only system identification method will be created to characterize the motion of the system about this periodic trajectory using linear time-periodic systems theory, and that will be used to find a mathematical model for the nonlinear system. A video-based motion capture system will be used to record the motion of a few subjects as they walk on an instrumented treadmill, and the measurements will be used to identify a reduced model for their neuromuscular function during gait. That model will then be incorporated into the computed muscle control forward dynamics algorithm in order to gain additional insights into the roles of individual muscles and the function of the neuromuscular system during gait.This work is expected to lead to improved treatments for gait disorders, potentially benefitting many of the thousands of people in the United States who currently suffer from these disorders. Common gait disorders may stem from birth defects, residual effects of a disease, such as polio, or from injuries sustained in athletic activities, accidents or military combat, and although numerous treatments have been proposed for gait disorders, it is currently very difficult to predict how effective treatment will be. This work is expected to increase our understanding of gait so that appropriate treatments can be chosen more reliably. Also, the framework that will be used in this work is general, so the methods developed can also be used to study other nonlinear systems such as vehicles, wind turbines, machinery, etc? A short course will be created based on the results of this research and it will be used to share these new methods with a broad audience.